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Decentralized MPC based Obstacle Avoidance for Multi-Robot Target Tracking Scenarios
August 2018 • Rahul Tallamraju, Sujit Rajappa, Michael J. Black, Kamalakar Karlapalem, Aamir Ahmad
In this work, we consider the problem of decentralized multi-robot target tracking and obstacle avoidance in dynamic environments. Each robot executes a local motion planning algorithm which is based on model predictive control (MPC). The planner is designed as a quadratic program, subject to constraints on robot dynamics and obstacle avoidance. Repulsive potential field functions are employed to avoid obstacles. The novelty of our approach lies in embedding these non-linear potential field functions as constraint…
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