A hierarchical long short term safety framework for efficient robot manipulation under uncertainty |
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| Affiliation: | 1. College of Engineering and Physical Sciences, Aston University, Birmingham, B47ET, UK;2. Department of Mechanical Engineering, The University of Auckland, Auckland, 1010, New Zealand;3. Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;4. Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;5. Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW), University of Stuttgart, Stuttgart, 70174, Germany;1. School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China;2. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;1. State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China;2. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China;3. School of Mechanical and Electrical Engineering, Shenyang Aerospace University, Shenyang 110136, China;1. Xidian University, Xi''an, China;2. KTH Royal Institute of Technology, Stockholm, Sweden;3. University of Patras, Patras, Greece;4. Technical University of Berlin, Berlin, Federal Republic of Germany;1. School of Mechanical Engineering, Shandong University, Jinan 250061, PR China;2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture at Shandong University, Ministry of Education, Jinan 250061, PR China |
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| Abstract: | Safe and efficient robot manipulation in uncertain clustered environments has been recognized to be a key element of future intelligent industrial robots. Unlike traditional robots that work in structured and deterministic environments, intelligent industrial robots need to operate in dynamically changing and stochastic environments with limited computation resources. This paper proposed a hierarchical long short term safety system (HLSTS), where the upper layer contains a long term planner for global reference trajectory generation and the lower layer contains a short term planner for real-time emergent safety maneuvers. Additionally, a hierarchical coordinator is proposed to enable smooth coordination of the two layers by compensating the communication delay through trajectory modification. The theoretical results verify that the long term planner can always find a feasible trajectory (feasibility guarantee); and the short term planner can guarantee safety in the probabilistic sense. The proposed architecture is validated in industrial settings in both simulations and real robot experiments, where the robot is interacting with randomly moving obstacles while performing a goal reaching task. Experimental results demonstrate that the proposed HLSTS framework not only guarantees safety but also improves task efficiency. |
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| Keywords: | Robot safety Safe control Hierarchical control Motion planning |
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