Intelligent Robotics and Applications

A new kind of functional electrical stimulation (FES) rehabilitation system is presented in this paper, which can assist the paralyzed patients caused by stroke to perform specific exercise following the therapist’s intention. The master-slave rehabilitation concept is firstly introduced into the FES system. This system consists of a master unit and a slave unit, and the two units are connected through wireless communication. Surface electromyography (sEMG) of the master side (therapist) is used as the control command for slave side (patients). Experiments are conducted on the upper limb of healthy subjects and the performance is satisfactory. The system exhibits four useful features: noninvasive technique, master-slave control, wireless communication, and "one to N" training mode.

A prescription-diagnosis function based on integrating support vector machine and generalized dynamic fuzzy neural networks (SVM-GDFNN) is developed to automatically recommend a suitable training mode to the impaired limb. Considering the outstanding generalization ability and misclassified samples mainly distributed nearby the support vector for SVM method, SVM is adopted to recommend a preliminary prescription diagnosis for the sample and GDFNN is employed to rediagnose the sample nearby the support vector. Finally, the training mode of impaired limb is prescribed according to the designed principles. In addition, wavelet packet decomposition is applied to extract the features representing the impaired-limb movement performance. Clinical experiment results indicate that the suggested method can effectively reduce the misdiagnosis and serve with a high diagnostic accuracy. Meanwhile, the designed rehabilitation system well manages the promising prescription-diagnosis function, improving the intelligent level.

Our ultimate goal is to develop autonomous mobile home healthcare robots which closely monitor and evaluate the patients’ motor function, and their at-home training therapy process, providing automatically calling for medical personnel in emergency situations. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs), and meanwhile, relieve therapists from great burden in canonical rehabilitation.

In order to achieve our ultimate goal, we have developed following programs/algorithms for monitoring subject activities and recognizing human behaviors. 1) Control programs for a mobile robot to track and follow human by three different viewpoints 2) Algorithms for measuring and analyzing of lower limb joints angle from RGB-D images from a Kinect sensor located at the mobile robot, and 3) Algorithms for recognizing gait gesture. In 2), compensation with colored marks was implemented to deal with the joint trajectory error caused by mixing-up and frame flying during tracking and following human movement by the mobile robot. In 3), We have proposed a Hidden Markov Model (HMM) based human behavior recognition using lower limb joint angles and body angle.

Experiment results showed that, joint trajectory could be analyzed with high accuracy compared to a motion tracking system, and human behavior could be recognized from the joint trajectory.

Decode the human motion intension precisely in real time is the key problem in coordinated control of the lower extremity exoskeleton. In this research, the relationship between frequency characteristics of sEMG (surface electromyographic) and muscle contraction is established in real time according to the biomechanism of skeletal muscle; DPSE (Differentiated Power Spectrum Estimation) method is applied to extract frequency characteristics from sEMG precisely and quickly; offset compensation is added to prevent noise disturbance during feature extracting of the sEMG with lower SNR (signal-to-noise ratio). Corresponding experiments on knee joint are conducted by prototype exoskeleton robot. EMGBFT (EMG Biofeedback therapy) based on force and haptic is applied as information feedback. Results show the human-machine interface can decode human motion intension and assist or resist movement of the wearer in real-time.

The previous perception and control system of smart wheelchairs normally doesn’t distinguish different objects and treats all objects as obstacles. Consequently it is hard to realize the object related navigation tasks such as furniture docking or door passage with interference from the obstacle avoidance behavior. In this article, a local 3D semantic map is built online using a low-cost RGB-D camera, which provides the semantic and geometrical data of the recognized objects to the shared control modules for user intention estimation, target selection, motion control, as well as parameters adjusting of weight optimization for addressing different target. With the object information provided by 3D semantic map, our control system can choose different behaviors according to user intention to implement object related navigation. A smart wheelchair prototype equipped with a Kinect is developed and tested in real environment. The experiments showed that the 3D semantic map-based shared control can effectively enhance the smart wheelchair’s mobility, and improve the collaboration between the user and the smart wheelchair.

Treatment for upper extremity impairment following a stroke or other conditions relies on rehabilitation programs, especially on passive arm movement therapy at the early stages of impairment. An exoskeleton robot (

ETS-MARSE

) was developed to be worn on the lateral side of upper-limb to rehabilitate and assist daily upper-limb motion. We have implemented a nonlinear sliding mode control technique to maneuver the

ETS-MARSE

in providing different passive rehabilitation exercises that include single and multi joint movement exercises. To evaluate the robustness and tracking performance of the controller, exercise involving healthy human subject were performed, where spasticity (a resistance) on arm movement which often found to subjects following a stroke was added artificially. Experimental results show the efficient performance of the controller to maneuver the exoskeleton to provide passive rehabilitation therapy.

This paper investigates the processing of surface electromyographic (sEMG) signals collected from the forearm of a human subject and, based on which, a control strategy is developed for an exoskeleton arm. In this study, we map the motion of elbow and wrist to the corresponding joints of an exoskeleton arm. Linear Discriminant Analysis (LDA) based classifiers are introduced as the indicator of the motion type of the joints, and then with the force of corresponding agonist muscles the control signal is produced. In the strategy, which is different from the conventional method, we assign one classifier for each joint, decomposing the motion of the two joints into independent parts, making the recognition of the forearm motion a combination of the results of different joints. In addition, training time is reduced and recognition of motion is simplified.

In the course of the demographic change companies will have to tackle the challenges of an ageing workforce. Since older employees, especially blue-collar workers are more likely to show an attrition of their working ability, manufacturers need to take preventive and compensative measures: first to maintain health and well being of their employees, second to integrate those with already reduced working ability and third to further increase productivity. On workplace level the concept of a production assistance robot offers a promising approach, combining support and relief for the worker with the benefits of automation directly in the value added chain. This paper summarizes several approaches, where adding simple low level intelligence to industrial robots results in economically and ergonomically effective assistance functions.

This paper proposes a functional electrical stimulation (FES)-involved control strategy for self-made exoskeleton lower limb rehabilitation robot for the training purpose of paraplegic patients caused by spinal cord injury (SCI) or stroke. Two muscles (Vastus Medialis and Riceps Femoris) are stimulated to produce active torque around knee joint which can be considered as a redundant actuator besides electrical motor. During the predefined trajectory tracking task, electrical motors compensate for the gravitational torque of the entire human-robot system, while the muscles provide torque calculated by a PD position/velocity controller based on the tracking error. The FES-induced torque control is accomplished with combination of feedforward and feedback controller, former of which is obtained by applying off-line trained neural networks to map the relationship between desired active torque and FES parameters. Simulation results obtained by using Simulink toolboxes in Matlab verify the feasibility of this control strategy.

This paper analyzes the kinematics of human upper-arm and develops a 6DOF exoskeleton upper-limb hemiplegic rehabilitation training robot. It describes the mechanical structure and implementation function of each module of the robot system, and it also describes a design for the movement data collection. The robot can assist the patient’s upper-limb to do active movement training which simultaneously involves multiple joints and a total of 7DOF of human upper-limb, that is, shoulder flexion/extension, shoulder abduction/adduction, shoulder internal rotation/external rotation, elbow flexion/extension, forearm supination/pronation, wrist extension/flexion and wrist ulnar deviation/radial deviation

The dynamic analysis and optimization problem of a 2-DoF Translational Parallel Manipulator (TPM) is addressed in this paper. Based on the principle of virtual work and the concept of link Jacobian matrix, the explicit expressions of the dynamic model of the 2-DoF TPM in the global task space are derived. Using the dynamic model, a global and comprehensive dynamic performance index (GCDPI) is proposed to evaluate the manipulator capabilities in terms of dynamic manipulability and dexterity in the prescribed task space. The dynamic optimization problem, which aims at providing the largest, the most isotropic and the most uniform dynamic manipulability of the 2-DoF TPM in the task space, is formulated as the minimization of GCDPI subjected to a set of appropriate constraints. Optimization results showed that the dynamic manipulability of the 2-DoF TPM with optimized kinematic and inertial parameters improves greatly in the prescribed task space. The dynamic equations are also incorporated in the hardware in the loop simulation of the 2-DoF TPM and experimental results show the tracking errors of the linear motor can be improved greatly when a nonlinear computed torque feedforward controller is implemented in addition to the cascade position controller.

Phosphor coating is one of the key steps in high-power LED packaging processes, among which the design of phosphor droplet jetting actuator is the pivotal technology. In this paper, the forming process of the phosphor droplets will be described, and a piezoelectric droplet printing actuator model about the phosphor fluid movement in the nozzle and the pressure cabin is used to define two criterions for producing phosphor droplets. These criterions can be used to design the piezoelectric actuator, the cabin structure and to select the piezoelectric actuator material. And all these developed models will help to understand the phosphor drop formation process and can be applied in phosphor jetting actuator designs.

OLED (Organic light-emitting) displays have been called the next generation of display devices for their unique properties: colorful images, large viewing angle, light weight and power efficiency. Complex manufacture processing makes the screen have some defects. Detecting the defects will help to improve the quality. In this paper we concentrate on detecting these defects and proposed a corner-points based method, where the corner-points are extracted from the skeleton image and used as the control points for the subtract operation. We proposed an improved Otsu method to determine the image segmentation threshold by recursive process. Based on the algorithm proposed, a system for OLED screen defect detection was developed. The test result shows that the developed system can detect most of the defects on the panel.

The fluid dispensing technology has been widely used to deliver all kinds of fluids in electronic industry. This paper first put forward an initial approach based on the direct driving principle to dispense the liquid with a high consistency and precision. According to the direct driving principle, the gas-liquid slug flow should be formed as a stable pattern in the micro-channel while the flow rate ratio between the gas and liquid is in an appropriate range. The linkage control strategy had been done to realize the two-phase flow during the dispensing process. The two-phase flow dispensing system had seven sub-systems for integration to achieve the multi-functions. The control sub-system is the most important unit applying the industry personal computer to connect and control other sub-systems. It undertakes three main tasks, communication, data processing and feed-back control. As a result, the stream of compressed air injected into the continuous liquid stream controlled by the peristaltic pump, the bubbles and droplets appeared in the micro-channel separately and uniformly.

Laser bonding technology is widely used in encapsulation field. However, the uneven temperature field in the laser bonding influences the bonding quality. This paper is to study the effect of temperature on the laser bonding quality. The designed system has a human-machine interface and its measurement accuracy reach±1

o

C. The multiple temperature measurement system is developed for laser bonding process based on K-type thermocouple. This system is composed of a host computer by PC software Visual Basic 6.0 and a lower controller whose core is MSP430F149. The host computer is used for human-machine interface interaction, controlling the lower controller through serial communication protocol. According to the instructions from the host computer, the lower controller executes the corresponding temperature measurement action, and then survey data from multi-channel thermocouples is transferred to the host computer through a serial port. The temperature can be displayed curves and saved. This system has wider measuring temperature range, higher temperature measurement precision and high sensitivity and can meet the transient temperature field measurement need of laser bonding. The temperature measurement range of the system is 0 to 1000

o

C and the measurement accuracy of the system reaches±1

o

C using the single chip MSP430F149 with 12-bit ADC module.

The magneto-rheological (MR) damper has been widely explored in the study of vibration suppression for vehicle suspension and constructional systems, etc. Aiming at semi-active controllable hysteretic nonlinear property of the MR damper depending on direct magnetic field, the generation mechanism of conducted and radiated electromagnetic interference (EMI) noises for intelligent vehicle system with MR dampers are initially proposed in this paper, which includes strong nonlinearities arisen from the semi-active control strategy, road surface shock excitations, high-frequency devices in control circuit, environmental electromagnetic (EM) field coupling to excitation coil, and excitation coil impedance mismatch of the MR damper. Upon above studies, both the conducted EMI noise model and the radiated EMI noise model are generally proposed for the MR damper and its control system, and the far field characteristic of radiated EM field generated from excitation coil of the MR damper is further analyzed. The results of simulation and experiment show correctness of the proposed EMI noise models, which will play an important role in future application study for the EMI noise suppression of intelligent vehicle suspension design with MR dampers.

For safe human-robot collaboration a technologically diverse and redundant sensor system is developed which comprises ultrasound sensors and two monocular camera systems. The sensor system recognizes human extremities in the collaboration area in which robot and human shall work together interactively. The robot controller calculates the shortest distance between the robot and a human operator. With the fused sensor data the controller determines how to adapt the robot behavior to avoid undesired physical contact with the human operator.

Robot assisted medical system has become one of the most important directions among robot studying field. This paper records a research on Multi-DOF pathological sampling flexible robot system which can be used in minimally invasive surgery. The main work includes: Overall structure design based on some special requirements, mathematical modeling and analysis, system hardware and software building, movement experiment and simulation capture experiment. Result of the experiments shows that the Multi-DOF pathological sampling flexible robot can fulfill the prospective design requirements and be capable for sampling and detecting.

This paper introduces new so-called control by 3D simulation concepts which are the basis for the simulation based development of complex control algorithms e. g. in the field of robotics and automation. Now, a controller design can be developed, parameterized, tested and verified using so called Virtual Testbeds until they perform adequately in simulation. Then a stripped down version of the same simulation system uses the same simulation model and the same simulation algorithms on the real hardware implementing a real-time capable controller. This results in an integrated development approach, which brings simulation technology on the real hardware to bridge the gap between simulation and real world operation. In this way, Virtual Testbeds and control by 3D simulation provide major building blocks in the emerging field of eRobotics to keep manageable the ever increasing complexity of current computer-aided solutions.

In this paper, we establish a time-varying fuzzy Markov model to estimate human intention for natural non-verbal human robot interface. Based on human posture information, we change the probability between states to improve the accuracy of estimation of human intention. The advantages of the approach are three fold: i) non-verbal information is core of natural interaction; ii) time-varying probability improves estimation accuracy; and iii) fuzzy inference consider practical human experience.

This study aims to contribute to improved road safety through development of a directional driver model. A comprehensive driver model incorporating path preview, prediction, muscular system dynamic, neural process, processing and sensory time delay, is formulated and coupled with a yaw-plane vehicle model. The coupled driver/vehicle model is analyzed to investigate path tracking performance and steering effort of human driver through variation of driving characteristics. Thus, a composite performance index which closely describes the tracking performance of the vehicle and driver’s steering effort has been formulated and minimized to obtain the control measures of human driver. The results illustrate that drivers with different driving skill could effectively reduce the path tracking error to a safe threshold level by minimizing the defined performance index. The results further suggest that drivers with higher level of driving skill employ less steering effort while performing a path tracking task.

Due to the high uncertainty of semiconductor manufacturing system, its rescheduling problems are extremely difficult to solve. In this paper, we investigate a novel single machine oriented match-up rescheduling (SMUR) method that implement the partial repair rescheduling in a dynamic manufacturing environment. Both of SMUR principle and algorithm are discussed. Its effectiveness has been verified by a simulation study. Computational results show that the proposed method has better stability and efficiency compared with the right-shift rescheduling method.

In the field of CNC machining, comparing with point milling, flank milling has a significant advantage in terms of processing efficiency. However, for machining of complex surfaces or large ruled surface, we have to divide the whole surface into different regions and then the flank milling is employed. With the method of sub-regional flank milling, we can achieve those goals. In this paper, iso-parametric method is used for dividing ruled surface into sub-regions and the LBM method for the tool path generation. In order to test and verify the accuracy of the proposed method, the tool path error is calculated by comparing the nominal surface with the one enveloped by the tool movement. Envelope theory of two-parameter family of spheres was used to get the envelope surface. Tool path error can be calculated by signed distance between the ruled surface and the envelope surface.

This paper presents the initial results achieved by the ROBOFOOT project aimed at contributing to the introduction of robotics in the Footwear Manufacturing Industry. In particular, user requirements, operations selected and technical achievements reached so far are described. Visual servoing solution developed for shoe pose identification is described with deeper detail. The introduction of this technology allows the coexistence of current working practices and robotic solutions, with minor changes in the production means already existing in most companies. This has been identified as one of the requirements by the end-users taking part in the project.

A multi-objective optimization problem has been proposed and developed in determination of the optimal combination of end milling process parameters. Experiments have been designed with five input cutting process parameters at five different levels. The values of surface roughness in both down milling process and up milling process are the required objective parameters. The Taguchi optimization technology coupled with Grey relational analysis has been applied for solving the proposed multi-objective optimization problem to achieve the desired machined surface quality characteristics. Simulation experiments give the optimal parametric combination. Furthermore, the modeling of machined surface topography on the texture profiles along the feed direction is formulated as a nonlinear programming problem with constrained conditions. Simulation experiments for the machined surface topography with the initial and optimal combination of end milling process parameters are implemented and the simulation results verify the feasibility of the proposed model and method.

In manufacturing, plunge milling is one of the most effective methods and widely used for material removal in rough and semi-rough machining while machining hard material. The cutting force in milling is very difficult and complex to predict, especially in plunge milling since there are many parameters acting as the design variables in the cutting force formulation. In this paper, an empirical formula is used for reference and a new cutting force model is developed in plunge milling of Inconel 718. The coefficients in the new formula are calibrated by the plunge milling cutting test, then an experiment is designed to confirm the new model. By using the proposed model, it’s easy to predict the cutting force in plunge milling with considerable accuracy. Furthermore, the new model provides advice for the selections of machining parameters, machine tools and cutters to ensure the safety and high-quality of manufacturing process.

The cutter runout is very common in machine milling and has a great effect on the surface accuracy. In this paper, a measurement of radial cutter runout in revolving milling tool is proposed by using the laser sensor. A laser beam is projected onto the milling tool edge and subsequently reflected. The diffuse reflection is captured by the sensor and the displacement between the cutter and the laser sensor is obtained. Based on the dynamic displacement, the cutter runout is calculated. The experimental results show that the radial cutter runout is dynamically varying in the constant rotation speed and the runout fluctuation largens with the increasing speed.

According to the feature of the magnetic actuation principle, now there are mainly three driving methods: one is alternating magnetic field, another is stationary gradient magnetic field and the last one is rotating magnetic field. This paper provides a detailed insight into the present-day state of microrobot technology and development on structure and electromagnetic actuation (EMA) systems. Firstly, the microrobot based on the three actuation methods is selectively elaborated respectively and the structure of EMA systems, microrobot characteristics and actuation principle are all analyzed and compared; finally some of the critical aspects of microrobot and EMA system design are considered. This paper shows that rotating magnetic field will be the most actuation promising method in the future biomedical application.

In this paper, a Hammerstein system is proposed to describe the rate-dependent hysteresis nonlinearity of a piezoelectric actuator. In this system, a MPI model represents the nonlinear static block and a second order linear system represents the linear dynamic block. The parameters identification method for the system is given. Comparison between the outputs of the system and experiment shows that the system can describe the rate-dependent hysteresis nonlinearity of the piezoelectric actuator in a wide range.

A modified particle swarm optimization algorithm (MPSO) is proposed in this paper. The algorithm is implemented to identify the parameters of the hysteresis nonlinearity, which is described by a modified Prandtl-Ishlinskii model. This new algorithm redefines the global best position and personal best position in the traditional PSO algorithm by an effective informed strategy, in order to balance the exploitation and exploration of the algorithm. Furthermore, a mutation operator is employed to increase the diversity of the particles and prevent premature convergence. Experiments have been conducted to verify the effectiveness of the proposed method. The comparisons with other variants of the PSO demonstrate that the identification of hysteresis based on the MPSO is effective and feasible.

A sub-millimeter scale coil is investigated as an alternative means to power electronics for small-scale robots. The AC voltage is induced by time-varying magnetic field. FEM analysis of employing magnetic field concentrators to increase the field density is carried out, concluding with their ineffectiveness to offset the occupied space. The choice of conductive versus non-conductive photoresist is investigated. The coil fabrication process is based upon three-dimensional, two-photon-absorption photolithography. Additional steps include metal sputtering, microlaser patterning and wire-bonding. The steps detailing the entire design process are described. With the coil occupying a volume of 0.45 pico m

3

, the maximum AC voltage of approximately 84 nV, with power density of about 1.96 mW per meter cube were measured. The study concludes with proposing ways to increase the induced voltage to a useable voltage of 2 V.

This paper presents a digital lock-in amplifier (DLIA) based technique to detect the template-substrate contact in electrochemical nanolithography. This technique is applied to a specially designed electrochemical nanolithography system for verification. The system adopts a macro-micro positioning setup consisting of a fine stepping motor to drive the macropositioning stage and a PZT(lead zirconate titanate, Pb[Zr

x

Ti

1 − x

]O

3

) actuator to drive the micropositioning stage. The template is mounted on a force-displacement sensing module which is attached to the PZT actuated micropositioning stage and the substrate is mounted on a holder which is merged in the solution. When the template approaches the substrate, it is controlled to oscillate at a certain frequency. Two capacitive displacement sensors are used to measure the template oscillation. Afterwards, a digital lock-in amplifier is adopted to separate the oscillation information from the raw signal. The contact is determined by monitoring the separated oscillation information. Finally, experiment tests are conducted to verify the effectiveness of the digital lock-in amplifier. Experimental results demonstrate that the developed DLIA technique makes the template-substrate contact to nanometer accuracy.

When combined with a piezoelectric actuator, a mechanical amplifier can achieve high resolution and long range motion. In this paper, a previously proposed compliant mechanical amplifier based on a symmetric five bar structure was studied for performance optimization. The amplifier was optimized based on its most significant design parameters with goals of large amplification ratio and high natural frequency. The design was also optimized for various load cases and over a range of input displacements. The optimization procedure validated the variability of the amplification based both on applied load, structure, and input displacement.

While treating the disease using the targeted drug delivery method, the effectiveness of a drug primarily depends on the disease affected area, targeted particles and drug control release of the drug. In this paper, an optimum or near optimum real time targeted drug delivery system is proposed. Targeted path planning algorithm for ferromagnetic nano particles based on particle swarm optimization approach and artificial magnetic field concepts used as virtual MRI (magnetic resonance Imaging) is proposed to solve the obstacle free targeted drug delivery process in a 3d virtual environment. At first stage 3d path planning scheme based on attractive and repulsive artificial potential field for obstacle free path in certain blood vessels is used. Later, an optimization process for all the discovered trajectories by combining particle swarm optimization algorithm is performed to generate an optimal path. Simulation results showed that proposed algorithm has higher success rate in targeting the drugs with a faster convergence rate towards the optimal solution.

The goal for the California State University, Fullerton (CSUF) Unmanned Utility Ground Robotic Vehicle (UUGRV) project is to create a fully autonomous multi-functional modular robotic platform to experiment various possible applications in the area of ground based robotics. To achieve full automation in both indoor and outdoor environment, the robot is equipped with Differential Global Positioning System, Inertial Measurement Unit, Laser Measurement Scanner, and a X-box Kinect for indoor application. The robot’s mechanical design features two independently driven wheels and pivoting casters to achieve differential drive. Speed reduction is achieved by using chain drives to allow flexibility in gear ratio for different applications. Currently, the robot is being constructed as an autonomous lawn mower and has won the 2012 ION (Institute of Navigation) robotic lawn mower competition in the static category. In the future, more hardware and software for different applications will be developed on this platform.

The paper presents an approach for localizing a mobile robot in a feature-based map using a 2D laser rangefinder and wheel odometry. As the presented approach is based on set membership methods, the localization result consists of sets instead of points, and is guaranteed to contain the true robot position as long as the sensor errors are absolutely bounded and a maximum number of measurement outliers can be assumed. It is able to cope with a multitude of measurement per time step compared to previous approaches. Moreover, the approach is capable of identifying and marking outlier points in the laser range scan. A real world experiment, where a mobile robot is moving in a structured indoor environment with previously unmapped static and dynamic obstacles shows the feasibility of the approach. It is shown that the true robot pose is always included in the solution set, which is computed in real time.

This paper proposes an adaptive control strategy for trajectory tracking of a Wheeled Mobile Robot (WMR) which consists of a suspended platform and a manipulator. When the WMR moves in the presence of friction and external disturbance, the trajectory can hardly be tracked accurately by applying the backstepping approach. For addressing this problem, considering the dynamic interaction, a dynamic model of the system is constructed by using Direct Path Method (DPM). An adaptive fuzzy control combined with backstepping approach based on the dynamic model is proposed. To track the trajectory accurately, a fuzzy compensator is proposed to compensate modeling uncertainty such as friction and external disturbance. Moreover, to reduce the approximation error and ensure the system stability, a robust term is added to the adaptive control law. Simulation results show the effectiveness and merits of the proposed control strategy in the counteraction of modeling uncertainty and the trajectory tracking.

In this paper, we propose an integer inverse kinematics method for multijoint robot control. The method reduces computational overheads and leads to the development of a simple control system as the use of fuzzy logic enables linguistic modeling of the joint angle. A small humanoid robot is used to confirm via experiment that the method produces the same cycling movements in the robot as those in a human. In addition, we achieve fast information sharing by implementing the all-integer control algorithm in a low-cost, low-power microprocessor. Moreover, we evaluate the ability of this method for trajectory generation and confirm that target trajectories are reproduced well. The computational results of the general inverse kinematics model are compared to those of the integer inverse kinematics model and similar outputs are demonstrated. We show that the integer inverse kinematics model simplifies the control process.

Enabling high speed navigation of Unmanned Ground Vehicles (UGVs) in unknown rough terrain where limited or no information is available in advance requires the assessment of terrain in front of the UGV. Attempts have been made to predict the forces the terrain exerts on the UGV for the purpose of determining the maximum allowable velocity for a given terrain. However, current methods produce overly aggressive velocity profiles which could damage the UGV. This paper presents three novel safer methods of force prediction that produce effective velocity profiles. Two models, Instantaneous Elevation Change Model (IECM) and Sinusoidal Base Excitation Model: using Excitation Force (SBEM:EF), predict the forces exerted by the terrain on the vehicle at the ground contact point, while another method, Sinusoidal Base Excitation Model: using Transmitted Force (SBEM:TF), predicts the forces transmitted to the vehicle frame by the suspension.

This paper investigates a new method of modeling and simulation of a two wheeled Mobile Manipulators (MMs) system each equipped with a 6 DOF arm. Such system modeled in Matlab/Simulink (Simmechanic) environment is used to transport objects without explicit communication between the MMs. MMs cooperation control has received big interest in the last few years and has been suggested for various applications such as tasks involving hazardous environments, explosive handling, and space operations. However most research in MMs cooperation has been performed within 2D flat terrain environment. In this paper MMs are considered working in 3D space and we use the nonholonomic characteristics of the robotic manipulators which has been neglected in previous work. This paper describes a control algorithm for two MMs cooperation executing cooperation’s tasks. The proposed approach uses common MM sensors. The paper includes the description of the proposed control mechanism that enables ground mobile manipulators to execute complex tasks in cooperation’s.

The use of mobile robots to collect the sensor readings required to generate radiation maps has the significant advantage of eliminating the risk of exposure that humans would otherwise face by collecting the readings by hand. In this work, a mobile robotic platform designed specifically to collect this information to synthesize radiation maps is presented. Details of the design are discussed, focusing in particular on the physical map generating capabilities of this new platform that are necessary to enable the generation of the radiation maps. The physical maps are generated using a laser range finder based implementation of Simultaneous Localization and Mapping (SLAM).

Ground traction is very important for balancing of two-wheeled robots. This paper examines whether limiting wheel slip to a nominal optimal value, as in conventional traction control, improves the performance of two-wheeled robots on low traction surfaces. For a particular robot and simulation conditions, comparing the baseline linear state feedback controller of the two-wheeled robot with and without traction control shows that conventional traction control is ineffective when stopping abruptly from a constant speed.

Traction control on a baseline controller decreases the maximum stable stopping speed on an ice-like surface. Compensating torque induced by traction control only partially recovers performance. On a hypothetical wet or lubricated surface with exaggerated Stribeck effect, traction control only slightly improves performance. Therefore traction control distinct from the balance and velocity LQR controller is ineffective, normally degrades overall performance, and motivates research for an alternative controller.

Nao humanoid robot from Aldebaran Robotics is equipped with an odometry sensor providing rather inaccurate robot pose estimates. We propose using Structure from Motion (SfM) to enable visual odometry from Nao camera without the necessity to add artificial markers to the scene and show that the robot pose estimates can be significantly improved by fusing the data from the odometry sensor and visual odometry. The implementation consists of the sensor modules streaming robot data, the mapping module creating a 3D model, the visual localization module estimating camera pose w.r.t. the model, and the navigation module planning robot trajectories and performing the actual movement. All of the modules are connected through the RSB middleware, which makes the solution independent on the given robot type.

In this paper, a graph-based hierarchical SLAM framework is proposed which ensures not only the high-speed operation of graph-based SLAM, but also feasibility of large-scale 3D map building. Both local and global level graph-based SLAM will be operated. They can be concurrently implemented in different computing units but must maintained communication which is called as a session. During each session, local level SLAM will create a pose-graph containing trajectory for mobile robot and information for local maps. To avoid communication congestion, raw density point cloud of each pose-node will be reduced into a sparser one by voxel grid filtering. When a session is closed, duo-graph strategy is executed to guarantee the consistency between successive local map. To associate massive local map information and closing loops in large-scale environment, graph-based algorithm will also be implemented in global level SLAM.

Two experiments are carried out in the real indoor environment. In the first experiment, SLAM process is greatly accelerated in this framework by distributing the whole SLAM task into different level SLAM entities: local level SLAM operated on robot and global on laptop. It shows that this framework is scalable and it can be implemented in CS(Client-Server) model. Second experiment is conducted in our biggest work office around which we control the robot traverse for three times. It demonstrates that this framework can simultaneously keep fast graph-based SLAM in local-end and generate consistent and convergent 3D map in global-end SLAM process.

LOCOBOT

(

www.locobot.eu

) is a European project funded in the first call of the “Factory of the future” in FP 7 (FoF.NMP.2010-1). LOCOBOT addresses strategic objective ― Plug-and-Produce components for adaptive control. The ‘Factories of the Future’ public-private partnership (PPP) is a joint initiative of the European Commission and the private sector to promote research in advanced manufacturing across Europe. Launched in early 2009, this major European initiative has embarked upon its first 25 research projects which will achieve their final results in 2013 and 2014. 5 of these 25 projects are related to the Topic of robotics and LOCOBOT is one of this 5 projects. LOCOBOT is a system which reaches above and beyond what is currently available for those working in the automotive industry: it incorporates a flexible robotic assistant platform to support and increase manual production processes, as well as the engineering tools required for its setup. Further, this project aims to improve the ergonomics in industrial production processes.

This paper presents the results of modelling, parameter identification and control of the rotational axes of a quadrotor robot. The modelling is done in Newton-Euler Formalism and has been published before. Contrarily, our method uses a Grey-Box-based, iterative parameter identification approach, the results of which can easily be reproduced and offers great accuracy. By neglecting nonlinear and cross-coupling effects, only three to four parameters have to be identified per axis, depending on the order of the motor dynamics. Based on the achieved results we were able to design an aggressive

$\mathcal{H_{\infty}}$

attitude controller, which shows superior performance to the normal PID-like controllers. With an anti-windup compensator based on Riccati–equations we are able to show exceptional input disturbance rejection, even with disturbances saturating the engines.

This paper addresses the problem of using a fleet of autonomous watercraft to create models of various water quality parameters in complex environments using intelligent sampling algorithms. Maps depicting the spatial variation of these parameters can help researchers understand how certain ecological processes work and in turn help reduce the negative impact of human activities on the environment. In our domain of interest, it is infeasible to exhaustively sample the field to obtain statistically significant results. This problem is pertinent to autonomous water sampling where hysteresis in sensors causes delay in obtaining accurate measurements across a large field. In this paper, we present several different approaches to sampling with cooperative vehicles to quickly build accurate models of the environment. In addition, we describe a novel filter and a specialized planner that uses the gradient of sensor measurements to compensate for hysteresis while ensuring a fast sampling process. We validate the algorithms using results from both simulation and field experiments with four autonomous airboats measuring temperature and dissolved oxygen in a lake.

In safety-critical and in space applications, high demands are made on the reliability of the involved systems. As autonomy could increase both the efficiency and the reliability of such systems, a reliable autonomous system could be beneficial for several robotic scenarios.

In this paper, the concept of a biologically inspired, robust behaviour control system is presented. The system includes components for prediction of actions to be executed and the evaluation of the action consequences. In its design process, particularly the occurence of unexpected situations was taken into account. The paper concludes with a presentation of preliminary simulation results and the evaluation setup that will be used in future tests to demonstrate the model properties.

Exploring an unknown environment with multiple robots requires an efficient coordination method to minimize the total duration. A standard method to discover new areas is to assign frontiers (boundaries between unexplored and explored accessible areas) to robots. In this context, the frontier allocation method is paramount. This paper introduces a decentralized and computationally efficient frontier allocation method favoring a well balanced spatial distribution of robots in the environment. For this purpose, each robot evaluates its relative rank among the other robots in term of travel distance to each frontier. Accordingly, robots are allocated to the frontier for which it has the lowest rank. To evaluate this criteria, a wavefront propagation is computed from each frontier giving an interesting alternative to path planning from robot to frontiers. Comparisons with existing approaches in computerized simulation and on real robots demonstrated the validity and efficiency of our algorithm.

Parallel robots have become an interesting alternative to serial robots due to their capability to perform certain tasks at high speed and precision. However, in order to fully exploit the theoretical capabilities of these mechanism, model-based, advanced control approaches are required. In this paper, the Extended CTC control approach is introduced. This scheme is based on the introduction of the data of the passive joint sensors on a CTC-based control law. Experimental validation on a 5R parallel manipulator prototype is provided in order to demonstrate the effectiveness of the approach.

We present a control scheme that does not require exact knowledge of the model of an underwater vehicle while maintaining robustness against both parameter uncertainties and environment disturbances. An important aspect of the proposed control is the relative simplicity of its implementation. To verify the effectiveness of the controller, we use an efficient simulator that takes into account the fluid velocity and acceleration without the explicit expression of the last term. Simulations shows the effectiveness of the proposed control law.

This paper proposes a sliding-mode observer based rotor flux estimation scheme for induction motors. The sliding-mode observer is designed to track the stator currents and the control signals of the observer are used to estimate the rotor flux. The proposed rotor flux estimation scheme utilizes the stator currents, but does not need the stator voltage. It has significant advantages in practical applications, especially for sensorless Field Oriented Control (FOC) of induction motors. Some simulations are carried out to validate the proposed rotor flux estimation scheme.

Analysis about a certain company’s gasoline engine crankshaft system with dynamics of multi-body, analysis about the crank which work conditions are worst with the forcing displacement method for finite element analysis, based on the finite element analysis results and the load history to analysis fatigue and Take the experimental verification. The results show that the results based on the finite element analysis of fatigue analysis and the experimental results were very close, and the analysis method is more simple and high accuracy.

The research realizes a fast and high-precision positioning control for a high acceleration X-Y platform using an embedded motion control system. The control algorithm consists of a PD controller which is designed by pole placement approach to implement the feedback control, a feed forward controller to improve the dynamic performance of the servo mechanical system and a disturbance observer to suppress the external disturbances. The model of the high acceleration platform, which is driven by permanent magnet linear synchronous motors (PMLSMs), is first identified by a time domain relay feedback test. Then, the three parts of the controller are designed based on the identified model. The coefficient quantization error and the computational truncation error are specially considered in the fix-point DSP platform, which makes the implementation feasible to run in the embedded motion system. Experimental results are presented to demonstrate the effectiveness of the proposed control algorithm.

Consider the problem of control selection in complex dynamical and environmental scenarios where model predictive control (MPC) proves particularly effective. As the performance of MPC is highly dependent on the efficiency of its incorporated search algorithm, this work examined hill climbing as an alternative to traditional systematic or random search algorithms. The relative performance of a candidate hill climbing algorithm was compared to representative systematic and random algorithms in a set of systematic tests and in a real-world control scenario. These tests indicated that hill climbing can provide significantly improved search efficiency when the control space has a large number of dimensions or divisions along each dimension. Furthermore, this demonstrated that there was little increase in search times associated with a significant increase in the number of control configurations considered.

In this paper, for the purpose of improving operation performance of multi-fingered hand and multiple robotic manipulators, a robust position synchronization mode-free sliding-mode control (SMC) strategy is proposed. By invoking the Lyapunov stability approach, the effectiveness of the proposed approach is testified to be robust while facing various disturbances and dynamic uncertainties. Besides, according to the practical application, the kinematic diversity is taken into consideration. We assume each individual in the multi-agent system to be with kinematic redundancy or without. Finally, we present computer simulation results to verify the effectiveness of the proposed algorithm.

In order to solve the problem of real-time communication for multi-axis in networked motion control systems(NMCSs), a field-programmable gate array (FPGA) based real-time solution is proposed. In the proposed solution, a hardware data processing strategy is designed and the data link layer of real-time communication is implemented on FPGA. Moreover, in order to decrease the forwarding delay, the forwarding of real-time communication data is shifted down to data link layer from application layer. Theoretical analysis and experimental results show that the FPGA-based real-time solution reduces jitter and delay of communication. After 20000 tests, each nodes delay is 1.180

μs

in average, which achieves the same real-time performance as EtherCAT.

This paper is devoted to designing a decentralized synchronous controller for networked multi-agent systems. In the proposed controller, due to the limitations of message scheduling and network bandwidth, position synchronization error is defined as a differential position error between current axis and its preceding one. It is proven that the proposed controller can asymptotically stabilize both position and synchronization errors to zero. In addition, a motion message estimator is adopted in the synchronous controller to reduce the effect of network-induced delays. Simulations are performed on a networked multi-axis machine tool to validate its effectiveness and demonstrate that it can achieve good contouring performance for the multi-axis trajectory tracking over the real-time network.

Many important real-world problems, such as patrol or search and rescue, could benefit from the ability to train teams of robots to coordinate. One major challenge to achieving such coordination is determining the best way for robots on such teams to communicate with each other. Typical approaches employ hand-designed communication schemes that often require significant effort to engineer. In contrast, this paper presents a new communication scheme called the

hive brain

, in which the neural network controller of each robot is directly connected to internal nodes of other robots and the weights of these connections are evolved. In this way, the robots can evolve their own internal “language” to speak directly brain-to-brain. This approach is tested in a multirobot patrol synchronization domain where it produces robot controllers that synchronize through communication alone in both simulation and real robots, and that are robust to perturbation and changes in team size.

This paper presents the field testing in virtual environments for performance evaluation of cooperative multi-robot systems. Once motions of robots, objects of interests are modeled, a real-like virtual environment is created. Robots are then physically linked to the virtual environment within a simulator and cooperatively operate in the environment. Unlike a real field testing, the virtual testing allows users to evaluate performance of cooperation of robots both in qualitative and quantitative ways. Additionally, due to its easiness of controlling the environmental conditions the virtual testing can be effectively utilized for testing multi robot cooperation under the same or different conditions. In this paper, a team of multiple robots are assigned to one or more missions in the virtual environment, and their cooperative performances are numerically analyzed within the simulator.

This paper presents a robust formation control method independent on noise of compass sensor. There are various formation control method for multi-robot system. These methods offer great way to keep the (d,

φ

)-formation. In real environment, however, heading angle of each robot is affected by noise of compass sensor. Because of this reason, follower can’t keep exact formation. In this paper, we suggest formation control method that uses PID controller to resolve this problem. And we also prove that PID controller is effect to reduce position error.

Few works only deal with telerobotics of mobile manipulators via the Internet. This paper consists of a contribution in this research field and describes an Internet-based multi-agent telerobotic system of such robots.

The developed system provides the operator with a human/robot interface, accessible via the Internet, for remote control of mobile manipulators. This interface displays all sensors data and video images delivered by the eye-in-hand IP camera. In addition, the interface allows the operator to perform primitive tasks, either separately by the manipulator or by the mobile base, or in cooperation by both of them.

The proposed telerobotic system is implemented on the

RobuTER/ULM

mobile manipulator. The validity of the system is demonstrated through telerobotic experiments of four primitive tasks via the Internet over a long distance.

This paper presents a control approach of mobile manipulators so that they can carry out the task of pulling doors open. The approach is split up into five sub-tasks (

i

) the door is located and the handle is recognized by using the sensors of the robot (

ii

) the robot moves towards the door while avoiding obstacles so that its gripper can reach the handle (

iii

) the manipulator grasps the handle of the door (

iv

) the manipulator twists the handle following a predefined trajectory and, finally, (

v

) the robot carries out a coordinated movement by requesting both of the manipulator and the mobile base to achieve the task.

The proposed approach is integrated into a multi-agent control architecture of mobile manipulators and implemented on

RobuTER/ULM

. Experimental results are presented and discussed to verify the performances of the approach.

This research presents a planar area calculation method, focusing on image warping to top view. An orientation sensor attached to a camera is used to acquire the camera’s orientation in real time. In practice, alignment between camera and sensor is imperfect. Therefore, calibration between camera and sensor is addressed using Iterative Least Square method. Then, extrinsic parameters derived from the calibrated sensor and pre-computed intrinsic parameters will be used to generate homography matrix. Homography matrix and a separately required translation matrix will be used to generate a top view image. In the top view image, we can directly count the number of target pixel. Finally, the number of pixel is converted to area size in real-world unit.

We propose a system for enhancing a human-robot interaction system. The goal is to embrace surrounding persons into a conversation with the robot by means of establishing or keeping eye contact. For this, a simple and hence computationally efficient people tracking algorithm has been developed, which in itself is an enhancement of existing approaches. As the foundation of our approach we use a vanilla Kalman filter that explicitly models the velocity in the state space, while the observations are transformed into a unified global coordinate system. We evaluate different integration strategies for multiple sensor cues. Furthermore, we extend an algorithm for group detection to be able to recognize individuals.

This paper presents a vision-tracking system for mobile robots, which travel in a 3-dimentional environment. The developed system controls pan and tilt actuators attached to a camera so that a target is always directly in the line of sight of the camera. This is achieved by using data from robot wheel encoders, a 3-axis accelerometer, a 3-axis gyroscope, pan and tilt motor encoders, and camera. The developed system is a multi-rate sampled data system, where the sampling rate of the camera is different with that of the other sensors. For the accurate estimation of the robot velocity, the developed system detects the slip of robot wheels, by comparing the data from the encoders and the accelerometer. The developed system estimates the target position by using an extended Kalman filter. The experiments are performed to show the tracking performance of the developed system in several motion scenarios, including climbing slopes and slip cases.

This paper presents a multiple target tracking method that uses the Dezert-Smarandache Theory (DSmT) for data association. A detailed framework is developed to show how the DSmT can be used to associate measurements with the corresponding correct targets. We will discuss the choices of the tracking hypotheses in the DSmT and we will demonstrate the effectiveness of the developed approach on simulated and real tracking scenarios that uses color and infrared cues.

In this paper, it is shown how robust execution of assembly skills can be planned by using sensor state space graphs. The here proposed method is evaluated by some assembly skills in which force feedback is applied. Assembly skills are implemented by manipulation primitive nets which constitute an interface between planning and execution of robotic systems. The sensor state space graph is introduced, which is an extension of the contact formation graph in a more general way, when various sensors might be used simultaneously for assembly execution. It is shown, how contact formation graphs can be generated by simulation of rigid body motions. The known contact formation graphs are enhanced by the definition of contact types between higher order surfaces. Additionally, a more general view is given by introducing sensor state space graphs. It is shown how contact formation graphs can be mapped to manipulation primitive nets, which allow the robust execution of assembly skills, despite the appearance of uncertainties. The approach is demonstrated successfully on some assembly tasks. Here the task of plugging a power socket on a top hat rail is illustrated due to its complex sequence. The shown assembly task is characterized by small fitting tolerances, where the application of force feedback is indispensable.