Learning Generalisable Coupling Terms for Obstacle Avoidance via Low-dimensional Geometric Descriptors
| Autor: | Michael Mistry, Yvan Petillot, Èric Pairet, Paola Ardón |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Control and Optimization Computer science Generalization Autonomous agent Biomedical Engineering 02 engineering and technology Machine learning computer.software_genre Computer Science - Robotics 020901 industrial engineering & automation Artificial Intelligence Robustness (computer science) Obstacle avoidance 0202 electrical engineering electronic engineering information engineering Manipulator Collision avoidance business.industry Mechanical Engineering Computer Science Applications Human-Computer Interaction Control and Systems Engineering Task analysis Robot 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business computer Robotics (cs.RO) |
| DOI: | 10.48550/arxiv.1906.09941 |
| Popis: | Unforeseen events are frequent in the real-world environments where robots are expected to assist, raising the need for fast replanning of the policy in execution to guarantee the system and environment safety. Inspired by human behavioural studies of obstacle avoidance and route selection, this paper presents a hierarchical framework which generates reactive yet bounded obstacle avoidance behaviours through a multi-layered analysis. The framework leverages the strengths of learning techniques and the versatility of dynamic movement primitives to efficiently unify perception, decision, and action levels via low-dimensional geometric descriptors of the environment. Experimental evaluation on synthetic environments and a real anthropomorphic manipulator proves that the robustness and generalisation capabilities of the proposed approach regardless of the obstacle avoidance scenario makes it suitable for robotic systems in real-world environments. Comment: Accepted for publication at the IEEE/RSJ International Conference on Intelligent Robots and Systems 2019 |
| Databáze: | OpenAIRE |
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