Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game
Autor: | Gafur, Nigora, Kanagalingam, Gajanan, Ruskowski, Martin |
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Rok vydání: | 2021 |
Předmět: | |
Druh dokumentu: | Working Paper |
DOI: | 10.1109/ACCESS.2022.3176626 |
Popis: | A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm is formulated as a non-cooperative game, where each robot is considered as an agent. Each agent optimizes its own motion and accounts for the predicted movement of surrounding agents. We propose a novel approach to formulate the dynamic collision constraints. Additionally, we account for deadlocks that might occur in a setup of multiple robotic manipulators. We validate our algorithm on a pick and place scenario for four collaborative robots operating in a common workspace in the simulation environment Gazebo. The robots are controlled by the Robot Operating System (ROS). We demonstrate, that our approach is real-time capable and, due to the distributed nature of the approach, easily scales to an arbitrary number of robot manipulators in a shared workspace. Comment: 12 pages, 11 figures |
Databáze: | arXiv |
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