In this paper we present work towards the benchmarking of mobile manipulation algorithms. We review the current state-of-the art in mobile manipulation and analyze the most prominent algorithms concerning common structures and sub-components. We propose and implement harmonized interfaces for those components, building upon existing software frameworks and libraries. The foundation on the same subcomponents makes it possible to evaluate mobile manipulation planning algorithms in a systematic way. In particular it enables us to investigate on the influence of different combinations of sub-components for the overall planning task, for which we present experiments in simulation.
To achieve autonomous mobile robot navigation, one of fundamental requirements is localization technique. It is difficult for any mobile robot to perform assigned task or sequence of tasks autonomously without accurate position knowledge relative to its environment. There are many existing approaches to accomplish localization in mobile robots but some of the existing mobile robot localization techniques can not be used in large indoor environments because of installation and environmental requirements. Many of existing indoor localization solutions costs significantly more as compared to the solution evaluated in this paper. In this paper a novel passive landmark based indoor position estimation technique is investigated for its robustness, accuracy, repeatability and reliability in large public environment. Use of passive artificial landmarks minimize the disturbance to the user, make the installation process easy, scalable and reduces the total system cost. A comprehensive testing arena is developed at Computer Science Department, University of Applied Sciences Bonn-Rhein-Sieg. This technique has been tested here under different environmental conditions i.e different lighting conditions, different sensor angles, different orientations and different ceiling heights. These tests are designed to subject this technique to possible unexpected and expected conditions that could arise in any large indoor public environment e.g supermarkets, museums etc. This makes our testing and experimental evaluation highly valuable before integrating this technique with mobile service robots at a large scale. This paper experimentally evaluates reliability, robustness and accuracy of this technique over other techniques.
