Online Distributed Trajectory Planning for Quadrotor Swarm with Feasibility Guarantee using Linear Safe Corridor
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This paper presents a new online multi-agent trajectory planning algorithm that guarantees to generate safe, dynamically feasible trajectories in a cluttered environment. The proposed algorithm utilizes a linear safe corridor (LSC) to formulate the distributed trajectory optimization problem with only feasible constraints, so it does not resort to slack variables or soft constraints to avoid optimization failure. Also, we adopt a priority-based goal planning method to prevent the deadlock without additional communication for decision making. The proposed algorithm can compute the trajectories for 60 agents on average 15.5 ms per agent with an Intel i7 laptop and can find the trajectory that reaches the goal without deadlock in both random forest and indoor space. We validated safety and operability of the proposed algorithm through a real flight test with ten quadrotors in a maze-like environment.
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