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Formation Tracking and Obstacle Avoidance for Multiple Quadrotors With Static and Dynamic Obstacles

Juntong Qi, Jinjin Guo, Mingming Wang, Chong Wu, Zhenwei Ma

2022IEEE Robotics and Automation Letters55 citationsDOI

Abstract

This letter proposes a novel distributed cooperative control algorithm to address the problem of collision avoidance and obstacle avoidance for multiple quadrotors during the formation tracking process. The proposed algorithm couples collision avoidance and obstacle avoidance schemes into the control layer. To avoid collisions between quadrotors in time, a repulsion function based on Hooke’s law with damping is proposed, which fully considers the relative position and relative velocity between quadrotors. In addition, based on the obstacle avoidance behavior of pigeons, a split-merge strategy is designed for multiple quadrotors to avoid static and dynamic obstacles. The split-merge strategy is driven by the relative position between the quadrotors and the obstacles, and it can calculate the optimal velocity to keep the quadrotors away from obstacles in the field of view. Several simulations and outdoor experiments for multiple quadrotors are presented to verify the effectiveness of the theoretical results.

Topics & Concepts

Merge (version control)Obstacle avoidanceCollision avoidanceControl theory (sociology)ObstacleComputer scienceRelative velocityCollisionPosition (finance)Control (management)Artificial intelligenceRobotMobile robotLawPhysicsEconomicsPolitical scienceInformation retrievalComputer securityFinanceQuantum mechanicsDistributed Control Multi-Agent SystemsAdaptive Control of Nonlinear SystemsRobotic Path Planning Algorithms
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