Downwash-Aware Trajectory Planning for Large Quadrotor Teams
arXiv:1704.04852
Abstract
We describe a method for formation-change trajectory planning for large quadrotor teams in obstacle-rich environments. Our method decomposes the planning problem into two stages: a discrete planner operating on a graph representation of the workspace, and a continuous refinement that converts the non-smooth graph plan into a set of C^k-continuous trajectories, locally optimizing an integral-squared-derivative cost. We account for the downwash effect, allowing safe flight in dense formations. We demonstrate the computational efficiency in simulation with up to 200 robots and the physical plausibility with an experiment with 32 nano-quadrotors. Our approach can compute safe and smooth trajectories for hundreds of quadrotors in dense environments with obstacles in a few minutes.
8 pages
Cited by in corpus (5)
- Trajectory Generation for Multiagent Point-To-Point Transitions via Distributed Model Predictive Control
- Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning
- Force-based Algorithm for Motion Planning of Large Agent Teams
- Fast and In Sync: Periodic Swarm Patterns for Quadrotors
- A Modular Framework for Motion Planning using Safe-by-Design Motion Primitives