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About this book

In this book, the capability map, a novel general representation of the kinematic capabilities of a robot arm, is introduced. The capability map allows to determine how well regions of the workspace are reachable for the end effector in different orientations. It is a representation that can be machine processed as well as intuitively visualized for the human. The capability map and the derived algorithms are a valuable source of information for high- and low-level planning processes. The versatile applicability of the capability map is shown by examples from several distinct application domains. In human-robot interaction, a bi-manual interface for tele-operation is objectively evaluated. In low-level geometric planning, more human-like motion is planned for a humanoid robot while also reducing the computation time. And in high-level task reasoning, the suitability of a robot for a task is evaluated.

Table of Contents

Frontmatter

1. Introduction

Current humanoid robots are mostly deployed in laboratory environments. However they are envisioned as helpful assistants in future households that e.g. enable elderly citizens to live independently in their homes by supporting them in their daily life. Possible service tasks are clearing the dish washer or setting the table. In this book a model of a robot arm’s workspace is developed. It is used to analyze the scene and a robot’s capabilities. In planning processes it serves as a source of information that supports the decision process.

Franziska Zacharias

2. Review of the Literature

In this chapter, the technical terms relevant for this work are introduced. Furthermore, on different levels of abstraction, components are described that are necessary for a service robot to solve manipulation tasks. The state of the art in high-level logical planning, also called task planning, is analyzed. Here the focus is on robotic manipulation problems. In the subsequent sections, it is analyzed how low-level planners like path planners, grasp planners and robot placement planners are used to solve the subtasks involved in manipulation, e.g. moving to an object, grasping it, and transporting it to a different position. It is examined whether knowledge representations are used to speed up or facilitate planning processes. Furthermore, it is outlined how the high-level and low-level planning can benefit from the use of knowledge representations.

Franziska Zacharias

3. Robot Performance Indices

Robot performance indices evaluate how well a robot can apply forces or move during a specific task or throughout the whole workspace. Hence, they potentially contribute to a general description of the versatile workspace that is the focus of this book. In this chapter, criteria used in robot arm design are compared and evaluated with respect to their objectives. It is identified whether these criteria provide measures to evaluate a robotic arm’s kinematic capabilities with respect to reachability and manipulation of objects throughout the workspace. It is determined whether they can be used to represent the robot arm workspace. Furthermore state of the art approaches to model the workspace are analyzed and evaluated.

Franziska Zacharias

4. Modeling the Robot Workspace

In general, every robot arm is designed differently, and therefore has different kinematic capabilities. These capabilities can result in directional structures specific to workspace regions. The robot’s ability to manipulate objects depends on the relative position of the objects. Two-handed manipulation is limited to a region where the workspaces of both arms overlap. The best performance is achieved in an even smaller subspace. In the previous chapter, requirements were identified that a representation of the reachability throughout the workspace has to fulfill. The

reachability

sphere

map

is a representation that meets these requirements. The choice of this name becomes clear later. It was first introduced in [117].

As a first step, the construction of the reachability sphere map is described. A visualization scheme is introduced for the representation. It allows the detection of structure in the workspace and enables its visualization. In a second step, a compact abstraction is proposed for the data of the reachability sphere map. The approach is illustrated using a DLR light weight arm (LWR ).

Franziska Zacharias

5. Visualization and Setup Evaluation

One field of application for the capability map is the visualization and inspection of the robot arm workspace. In this chapter, the workspace is visualized for several robot arms and discussed with respect to potential tasks. Furthermore, the capability map is used to objectively evaluate the quality of a setup for human robot interaction.

Franziska Zacharias

6. Application in Planning

This chapter demonstrates the use of the capability map in planning tasks. Using two examples, it is demonstrated how the capability map can be used to restrict the search space. The algorithms thus address the gap between task planning and path planning that is indicated in Figure 6.1 by the red rectangle. In the first application covered in this chapter a robot is placed to perform a given trajectory. Its suitability for the task is evaluated. In the second application the capability map is used to obtain good parameters for a path planner and bias the path planning process.

Franziska Zacharias

7. Conclusion and Outlook

This chapter summarizes the achievements presented in this book, provides some concluding remarks as well as an outlook on potential future applications and future research directions.

Franziska Zacharias

Backmatter

Additional information