Autonomous 6D-Docking and Manipulation with Non-Stationary-Base Using Self-Reconfigurable Modular Robots
Luenin Barrios, Thomas Collins, Robert Kovac, and Wei-Min Shen. Autonomous 6D-Docking and Manipulation with Non-Stationary-Base Using Self-Reconfigurable Modular Robots. In Proc. 2016 IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems, Daejeon, Korea, October 2016.
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Abstract
Aggregation of self-reconfigurable robotic modules can potentially offer many advantages for robotic locomotion and manipulation. The resulting system could be more reliable and fault-tolerant and provide the necessary flexibility for new tasks and environments. However, self-aggregation of modules is a challenging task, especially when the alignment of the docking parties in a 3D environment involves both position and orientation (6D), since the bases of docking may be non-stationary (e.g., floating in space, underwater, or moving along the ground), and the end-effectors may have accumulated uncertainties due to many dynamically-established connections between modules. This paper presents a new framework for docking in such a context and describes a solution for sensor- guided self-reconfiguration and manipulation with non-fixed bases. The main contributions of the paper include a realistic experiment setting for 6D docking where a modular manipulator is floating or rotating in space with a reaction wheel and searches and docks with a target module using vision. The movement of the docking parties is a combination of floating and manipulation, and the precision of the docking is guided by a sensor located at the tip of the docking interface. The docking itself is planned and executed by a real-time algorithm with a theoretical convergence boundary. This new framework has been tested in a high-fidelity physics-based simulator, as well as by real robotic modules based on SuperBot. Experimental results have shown an average success rate of more than 86.7 percent in a variety of different 6D-docking scenarios.
BibTeX Entry
@InProceedings{barrios2016-Autonomous-6D-Docking-and-Manipulation-with-Non-Stationary-Base-Using-Self-Reconfigurable-Modular-Robots,
abstract = {Aggregation of self-reconfigurable robotic modules can potentially offer many advantages for robotic locomotion and manipulation. The resulting system could be more reliable and fault-tolerant and provide the necessary flexibility for new tasks and environments. However, self-aggregation of modules is a challenging task, especially when the alignment of the docking parties in a 3D environment involves both position and orientation (6D), since the bases of docking may be non-stationary (e.g., floating in space, underwater, or moving along the ground), and the end-effectors may have accumulated uncertainties due to many dynamically-established connections between modules. This paper presents a new framework for docking in such a context and describes a solution for sensor- guided self-reconfiguration and manipulation with non-fixed bases. The main contributions of the paper include a realistic experiment setting for 6D docking where a modular manipulator is floating or rotating in space with a reaction wheel and searches and docks with a target module using vision. The movement of the docking parties is a combination of floating and manipulation, and the precision of the docking is guided by a sensor located at the tip of the docking interface. The docking itself is planned and executed by a real-time algorithm with a theoretical convergence boundary. This new framework has been tested in a high-fidelity physics-based simulator, as well as by real robotic modules based on SuperBot. Experimental results have shown an average success rate of more than 86.7 percent in a variety of different 6D-docking scenarios.},
address = {Daejeon, Korea},
author = {Luenin Barrios and Thomas Collins and Robert Kovac and Wei-Min Shen},
booktitle = iros-16,
month = oct,
title = {Autonomous 6D-Docking and Manipulation with Non-Stationary-Base Using Self-Reconfigurable Modular Robots},
year = {2016}
}
