Towards Autonomous Robotic Systems

Robot with non-back-drivable actuators will appear stiff when in contact with the environment and human. This scenario is unsafe for the Human-Robot Interaction (HRI). In order to guarantee safety in HRI, the robot will be made “soft” such that a compliant control can be introduced. Apart from utilizing the proper mechanism design, the back drivability actuators can be achieved by a suitable choice of control. In particular, in this paper, a PID control is employed to achieve an active compliance control. The reference impedance model characteristics are exploited for which the system allows us to introduce a virtual mass-spring-damper system to adjust the compliant control level. The performance of the PID control will be tested on the RED Hand in the simulation. The results are recorded and analyzed for the thumb finger. The results show that the PID controller is capable of controlling the motion and position of the RED Hand. In addition, the compliance behavior for the RED Hand can be suitably adjusted based on the required compliant level.

This study presents (1) the design and validation of a wearable sensor suite for the unobtrusive capture of heterogeneous signals indicative of the primary symptoms of Parkinson’s disease; tremor, bradykinesia and muscle rigidity in upper extremity movement and (2) a model to characterise these signals as they relate to the symptom severity as addressed by the Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS).The sensor suite and detection algorithms managed to distinguish between the non-mimicked and mimicked MDS-UPDRS tests on healthy subjects (p $$\le $$ 0.15), for all the primary symptoms of Parkinson’s disease. Future trials will be conducted on Parkinsonian subjects receiving deep brain stimulation (DBS) therapy. Quantifying symptom severity and correlating severity ratings with DBS treatment will be an important step to fully automate DBS therapy.

Industries such as flexible manufacturing and home care will be transformed by the presence of robotic assistants. Assurance of safety and functional soundness for these robotic systems will require rigorous verification and validation. We propose testing in simulation using Coverage-Driven Verification (CDV) to guide the testing process in an automatic and systematic way. We use a two-tiered test generation approach, where abstract test sequences are computed first and then concretized (e.g., data and variables are instantiated), to reduce the complexity of the test generation problem. To demonstrate the effectiveness of our approach, we developed a testbench for robotic code, running in ROS-Gazebo, that implements an object handover as part of a human-robot interaction (HRI) task. Tests are generated to stimulate the robot’s code in a realistic manner, through stimulating the human, environment, sensors, and actuators in simulation. We compare the merits of unconstrained, constrained and model-based test generation in achieving thorough exploration of the code under test, and interesting combinations of human-robot interactions. Our results show that CDV combined with systematic test generation achieves a very high degree of automation in simulation-based verification of control code for robots in HRI.

This paper explores three fundamental attributes of the Robokind Zeno-R25 (its status as person or machine, its ‘gender’, and intensity of its simulated facial expressions) and their impact on children’s perceptions of the robot, using a one-sample study design. Results from a sample of 37 children indicate that the robot is perceived as being a mix of person and machine, but also strongly as a male figure. Children could label emotions of the robot’s simulated facial-expressions but perceived intensities of these expressions varied. The findings demonstrate the importance of establishing fundamentals in user views towards social robots in supporting advanced arguments of social human-robot interaction.

This paper describes the design of a computational vision framework inspired by the cortices of the brain. The proposed framework carries out visual saliency and provides pathways through which object segmentation, learning and recognition skills can be learned and acquired through experience.

LARMbot project aims to develop a humanoid robot with biomimetic inspiration from human anatomy by using parallel mechanisms. Previous related work is presented particularly referring to torso and leg modules. A specific design of LARMbot is proposed by using proper parallel mechanisms in torso and leg designs. A CAD model is elaborated in SolidWorks® environment and the corresponding prototype is fabricated with low-cost user-oriented features by using commercial components and parts manufactured using 3D printing. Preliminary results of experiment tests are also reported for operation evaluation and architecture design characterization.

Sensors take measurements and provide feedback to the user via a calibrated system, in soft sensing the development of such systems is complicated by the presence of nonlinearities, e.g. contact, material properties and complex geometries. When designing soft-sensors it is desirable for them to be inexpensive and capable of providing high resolution output. Often these constraints limit the complexity of the sensing components and their low resolution data capture, this means that the usefulness of the sensor relies heavily upon the system design. This work delivers a force and topography sensing framework for a soft sensor. A system was designed to allow the data corresponding to the deformation of the sensor to be related to outputs of force and topography. This system utilised Genetic Programming (GP) and Model Order Reduction (MOR) methods to generate the required relationships. Using a range of 3D printed samples it was demonstrated that the system is capable of reconstructing the outputs within an error of one order of magnitude.

We report on experiences in the development of hybrid autonomous systems where high-level decisions are made by a rational agent. This rational agent interacts with other sub-systems via an abstraction engine. We describe three systems we have developed using the EASS BDI agent programming language and framework which supports this architecture. As a result of these experiences we recommend changes to the theoretical operational semantics that underpins the EASS framework and present a fourth implementation using the new semantics.

This paper reports the experimental evaluation of a Multi-Modal User Interface (MMUI) designed to enhance the user experience in terms of service usability and to increase acceptability of assistive robot systems by elderly users. The MMUI system offers users two main modalities to send commands: they are a GUI, usually running on the tablet attached to the robot, and a SUI, with a wearable microphone on the user. The study involved fifteen participants, aged between 70 and 89 years old, who were invited to interact with a robotic platform customized for providing every-day care and services to the elderly. The experimental task for the participants was to order a meal from three different menus using any interaction modality they liked. Quantitative and qualitative data analyses demonstrate a positive evaluation by users and show that the multi-modal means of interaction can help to make elderly-robot interaction more flexible and natural.

Research into the autonomy of small Unmanned Aerial Vehicles (UAVs), and especially on Vertical Take Off and Landing (VTOL) systems has intensified significantly in recent years. This paper develops a generic model of a VTOL UAV in symbolic form. The novelty of this work stems from the designed Model Predictive Control (MPC) algorithm based on this symbolic model. The MPC algorithm is compared with a state-of-the-art Linear Quadratic Regulator algorithm in attitude rate acquisition and its more accurate performance and robustness to noise is demonstrated. Results for the controllers designed for each of the aircraft’s angular rates are presented in response to input disturbances.

The rescue services face numerous challenges when entering and exploring dangerous environments in low or no visibility conditions and often without meaningful auditory and visual feedback. In such situations, rescue-personnel may have to rely solely on their own immediate haptic feedback in order to make their way in and out of a burning building by running their hands along the wall as a means of navigation. Consequently, the development of technology and machinery (robot) to support exploration and aid navigation would provide a significant benefit to the search and rescue operation; enhancing the capabilities of the fire and rescue personal and increasing their ability to exit safely [1]. A brief review and analysis of the previous published literature on exploring environments in low or no visibility conditions where haptic feedback has been utilized is provided and the design of a new intelligent haptic rein is proposed.

In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment. As a unique and essential parts of the warehouse, pillars from storing shelves are chosen as landmark objects for representing the environment. The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage image analysis method. Localization of the drone relies on PTAM algorithm. The system is implemented in Robot Operating System(ROS) and MATLAB, and has been successfully tested in real-world experiments. The result map after scaling has a metric error less than 20 cm.

Robot swarms are collections of simple robots cooperating without centralized control. Control algorithms for swarms are often inspired by decentralised problem-solving systems found in nature. In this paper we conduct a formal analysis of an algorithm inspired by the foraging behaviour of ants, where a swarm of flying vehicles searches for a target at some unknown location. We show how both exhaustive model checking and statistical model checking can be used to check properties that complement the results obtained through simulation, resulting in information that would facilitate the logistics of swarm deployment.

A framework for considering the stability of bilateral telemanipulator systems is considered. The approach adapts the work of Lawrence [3] to use a state-space formulation thus simplifying the identification of the stability conditions from the eigenvalues of the feedback system. Both numerical and symbolic stability conditions are considered.

This paper addresses the problem improving response times of robots implemented in the Robotic Operating System (ROS) using formal verification of computational-time feasibility. In order to verify the real time behaviour of a robot under uncertain signal processing times, methods of formal verification of timeliness properties are proposed for data flows in a ROS-based control system using Probabilistic Timed Programs (PTPs). To calculate the probability of success under certain time limits, and to demonstrate the strength of our approach, a case study is implemented for a robotic agent in terms of operational times verification using the PRISM model checker, which points to possible enhancements to the operation of the robotic agent.

The paper introduces the Psi Swarm robot, a platform developed to allow both affordable research in swarm robotics and versatility for teaching programming and robotics concepts. Motivated by the goals of reducing cost and construction complexity of existing swarm platforms, we have developed a trackable, sensor-rich and expandable platform which needs only a computer with internet browser to program. This paper outlines the design of the platform and the development of a tablet-computer based programming environment for the robot, intended to teach primary school aged children programming concepts.

Area coverage is a well-known problem in multi robotic systems, and it is a typical requirement in various real-world applications. A common and popular approach in the robotic community is to use explicit forms of communication for task allocation and coordination. These approaches are susceptible to the loss of communication signal, and costly with high computational complexity. There are very few approaches which are focused on implicit forms of communication. In these approaches, robots rely only on their local information for task allocation and coordination. In this paper, a cooperative strategy is proposed by which a team of robots perform spraying a large field. The focus of this paper is to achieve task allocation and coordination using only the robots’ local information.

One of the crucial questions to develop Autonomous Mobile Robotic systems is the energy consumption, its monitoring and management all along the mission. Mission complexity and fault tolerance capabilities require to exploit system redundancies, in terms of algorithms and hardware recruitment. This choice has an evident impact on energy consumption. This paper proposes an identification protocol to establish the energy consumption models for each control configuration of a Pioneer 3DX. These models are destined to be used as online predictors providing an estimation of the necessary remaining energy that mission success ‘nominally’ requires. At the end, the proposed energy consumption models are validated and discussed experimentally.

Mission performance is a large concept. It is rarely addressed in the context of autonomous mobile robotics. This paper proposes a generic framework addressing the concept of performance for autonomous mobile robotic mission. Moreover it presents an approach to manage the mobile robot hardware and software resources during the mission execution according to performance objectives. Simulation results illustrate the proposed approach on a patrolling mission example.

We study how a human operator can guide a swarm of robots when transporting a large object through an environment with obstacles. The operator controls a leader robot that influences the other robots of the swarm. Follower robots push the object only if they have no line of sight of the leader. The leader represents a way point that the object should reach. By changing its position over time, the operator effectively guides the transporting robots towards the final destination. The operator uses the Google Glass device to interact with the swarm. Communication can be achieved via either touch or voice commands and the support of a graphical user interface. Experimental results with 20 physical e-puck robots show that the human–robot interaction allows the swarm to transport the object through a complex environment.

We report a bio-inspired control model to dynamically self-organize a swarm robots system into unplanned patterns emerged through an aggregation method based upon using virtual viscoelastic links among the K-nearby robots. By varying this neighbourhood relationship, virtual viscoelastic links are dynamically created and destroyed between the robots and their sensed neighbours. Based on the equilibrium between these virtual links, the model can distribute the robots at equal angular configurations of the emergent shape being formed. A forward dependent angular motion control is designed to control at which speeds the robots are moving. The model is implemented and tested using the ARGoS simulator where many emerged self-organized configurations are formed showing the effectiveness of the model.

We present a portable active binocular robot vision architecture that integrates a number of visual behaviours. This vision architecture inherits the abilities of vergence, localisation, recognition and simultaneous identification of multiple target object instances. To demonstrate the portability of our vision architecture, we carry out qualitative and comparative analysis under two different hardware robotic settings, feature extraction techniques and viewpoints. Our portable active binocular robot vision architecture achieved average recognition rates of 93.5 % for fronto-parallel viewpoints and, 83 % percentage for anthropomorphic viewpoints, respectively.

There have been numerous attempts to develop anthropomorphic robotic hands with varying levels of dexterous capabilities. However, these robotic hands often suffer from a lack of comprehensive understanding of the musculoskeletal behavior of the human thumb with integrated foldable palm. This paper proposes a novel kinematic model to analyze the importance of thumb-palm embodiment in grasping objects. The model is validated using human demonstrations for five precision grasp types across five human subjects. The model is used to find whether there are any co-activations among the thumb joint angles and muskuloskeletal parameters of the palm. In this paper we show that there are certain pairs of joints that show stronger linear relationships in the torque space than in joint angle space. These observations provide useful design guidelines to reduce control complexity in anthropomorphic robotic thumbs.

The focus of this paper is on secure cloud service platform for mobile robots ecosystem. Especially the emphasis is based on the scope of open-source software frameworks such as Apache Hadoop which offers numerous possibilities to employ open-source designing tools and deployment models for private cloud computing planning. This paper presents implementation of the OpenCRP (Open CloudRobotic Platform) locally-operated private cloud infrastructure and configuration methods by using Hadoop distributed file system (HDFS) for easing the ecosystem communications set-up in its entirety. For robot teleoperation, ROS (Robot Operating System) is used. The presented ecosystem utilizes security features for autonomous cloud robotic platform, software tools to manage user authentication and methods for large-scale robot-based data management and analysis. In addition to robot trial set-up of robot data storage and sharing, an ecosystem built with two low-cost mobile robots is presented.

This paper describes a robot that performs person search in an office environment. The system brings together a number of technologies to ensure efficient and robust search in the face of varying conditions. These include face detection, face recognition, speech recognition, localization, path planning and re-planning in the presence of dynamic obstacles, and a decision theoretic search strategy. The main novel contribution of the system is an ensemble method for combining the outputs of multiple classifiers for face recognition. A second contribution is the use of a strong priority over the location of individuals in the database to guide search. The system is also able to use speech generation and recognition to interact with individuals to achieve its goals, as well as to receive goals via a mobile interface.

The low automation level of industrial manufacturing processes, in conjunction with the limited research in the field of object manipulation for placing tasks, rise the need for adaptive and accurate industrial robotic systems that can manipulate a variety of objects in an uncertain environment. We deal with those issues by providing insights into two modules of a skilled-based architecture, the SkiROS. Those modules are applied on the placing part of an industrial kitting operation and can lead to versatile perception of the environment and the accurate placing of objects in confined areas. We evaluate both modules in terms of accuracy, execution time and success rate in various setups of the environment. Also we evaluate the whole kitting pipeline – including the proposed modules – as a unit in terms of repeatability and execution time. The results show that the proposed system is capable to both accurately localize the kitting box and place the object in its narrow compartments.

We present a plugin for the ARGoS robot simulator which enables the use of 3D physics simulation and definition of objects and entities without the need to develop new entities in C++. We provide the facility for entities to be loaded and added to simulations using a URDF inspired XML format. Loading of entities, physics simulation and rendering is all handled by the plugin, removing the need for knowledge of specific engines or OpenGL. This paves the way for ARGoS to be used not only for development and evaluation of controllers but also for evolution of robot morphologies and co-evolution of controllers and morphologies which was previously not possible without a considerable development overhead.

This paper gives the first results from a research programme that aims to develop efficient navigation techniques for long range Autonomous Underwater Vehicles (AUVs) conducting ocean basin transits using low power sensors. The results results relate to the development of and on-line and low power cooperative navigation scheme between an AUV and an Unmanned Surface Vehicle (USV), where the latter acts as an acoustic tether for localization error reduction. Most of the computations are executed on the USV in order to reduce the power requirements of the AUV. The methodology is assessed by numerical simulation, where the Dead Reckoning (DR) error is modelled using data obtained from field trials and the result show that considerable estimation error reduction is possible even in very deep water operations.

This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On average, the counting and allocation algorithm correctly assigns 95 % of the robots in the swarm. The time to count the number of robots increases, on average, linearly with the number of robots, provided they are arranged in random formation.

This paper presents the results of an experiment that investigates the presence of cues in the signal generated by a low-cost Force Sensitive Resistor (FSR) to recognise surface texture. The sensor is moved across the surface and the data is analysed to investigate the presence of any patterns. We show that the signal contains enough information to recognise at least one sample surface.

In this paper we present the results of a preliminary study conducted to investigate the acceptance of a robotic shopping assistant among elderly people. The results show that most participants acclaim the development of assistive robots.

The work presented here investigates the impact of certain environmental parameters on the performance of a multi-robot team conducting exploration tasks. Experiments were conducted with physical robots and simulated robots, and a diverse set of metrics was computed. The experiments were structured to highlight several factors: (a) single-robot versus multi-robot tasks; (b) independent versus dependent (or “constrained”) tasks; and (c) static versus dynamic task allocation modes. Four different task allocation mechanisms were compared, in two different exploration scenarios, with two different starting configurations for the robot team. The results highlight the distinctions between parameterised environments (characterised by the factors above, the robots’ starting positions and the exploration scenario) and the effectiveness of each task allocation mechanism, illustrating that some mechanisms perform statistically better in particular environment parameterisations.

3D laserscanners are well suited sensors for different perception tasks like navigation and object recognition. However, ready-to-use 3D laserscanners are expensive and offer a low resolution as well as a small field of view. Therefore, many groups design their own 3D laserscanner by rotating a 2D laserscanner. Since this whole process is done frequently, this paper aims at fostering other groups’ future research by offering a list of necessary hardware including an online-accessible mechanical drawing, and available software. As it is possible to align the rotation axis and the 2D laserscanner in many different ways, we present an approach to optimize these orientations. A corresponding Matlab toolbox can be found at our website. The performance of the 3D laserscanner is shown by multiple matched point clouds acquired in outdoor environments.

Electro-adhesion is the new technology for constructing gripping solutions that can be used for automation of pick and place of a variety of materials. Since the technology works on the principle of parallel plate capacitors, there is an inherent ability to store charge when high voltage is applied. This causes an increased release time of the substrate when the voltage is switched off. This paper addresses the issue of residual charge and suggests ways to overcome the same, so that the performance of the gripper can be improved in a cycle of pick and release. Also a new universal equation has been devised, that can be used to calculate the performance of any gripping solution. This equation has been used to define a desired outcome (K) that has been evaluated for different configurations of the suggested electro-adhesive gripper.

Fault detection and identification methods (FDI) are an important aspect for ensuring consistent behavior of technical systems. In robotics FDI promises to improve the autonomy and robustness. Existing FDI research in robotics mostly focused on faults in specific areas, like sensor faults. While there is FDI research also on the overarching software system, common data sets to benchmark such solutions do not exist. In this paper we present a data set for FDI research on robot software systems to bridge this gap. We have recorded an HRI scenario with our RoboCup@Home platform and induced diverse empirically grounded faults using a novel, structured method. The recordings include the complete event-based communication of the system as well as detailed performance counters for all system components and exact ground-truth information on the induced faults. The resulting data set is a challenging benchmark for FDI research in robotics which is publicly available.

Staged at Piombino, Italy in September 2015, euRathlon 2015 was the world’s first multi-domain (air, land and sea) multi-robot search and rescue competition. In a mock-disaster scenario inspired by the 2011 Fukushima NPP accident, the euRathlon 2015 Grand Challenge required teams of robots to cooperate to map the area, find missing workers and stem a leak. In this paper we outline the euRathlon 2015 Grand Challenge and the approach used to benchmark and score teams. We conclude the paper with an evaluation of both the competition and the performance of the robot-robot teams in the Grand Challenge.

In face recognition, the large sizes of training databases can place a heavy burden on computing resources and may produce unsatisfactory results due to significant amount of irrelevant features for target screening. We adopt the technology of wireless sensor networks by storing semantic information in wireless tags to assist grouping of candidates. The semantic information of nearby people such as gender and race is provided to the robot and help it narrows its search to a smaller subset of the database. Hence the face recognizer can be simplified by training the selected subset samples that makes online training possible. Furthermore, the feature space can be constantly adjusted benefiting from online training to distinguish faces with higher accuracy and the resolution of training samples can also be adjusted based on the camera and target distance. In order to further improve the correct rate, permutation post processing has been employed. The proposed hybrid approach has been validated in experiments with a promising low error rate. Compared to other face recognition systems, our system is better suited to work on a human-machine interactive robot which needs to detect targets under different illumination conditions and from different distances.

In this paper, the localisation capabilities of ultra-wideband (UWB) communication devices are evaluated. A test platform is designed to perform experiments in indoor environments, to record the data for different node set-ups and to evaluate the results in practice. The platform development comprises hardware design of the anchor and tag node, development of the PC software for communication to the nodes, collecting the measured distance data and performing localisation algorithms. At the end, some experiments are performed in both line of sight (LOS) and non-line of sight (NLOS) cases with blocking and non-blocking barriers. The experiment results confirm a distance measurement accuracy of 10 cm in LOS conditions for 85 % of the measured distances in the range of 0.5 m to 30 m. In NLOS cases an additional offset can be observed in the measurement results causing a higher relative error for short distances.