ROSYApr 11, 2019

Technical Report: Safe, Aggressive Quadrotor Flight via Reachability-based Trajectory Design

arXiv:1904.05728v250 citations
Originality Incremental advance
AI Analysis

This work improves safety and efficiency for quadrotor applications like inspection and search-and-rescue by reducing conservatism in planning, though it is incremental as it builds on existing reachability-based methods.

The paper tackles the problem of ensuring safe quadrotor flight in cluttered environments by addressing conservative obstacle dilation in existing planners, using Reachability-based Trajectory Design (RTD) with zonotopes to account for trajectory-dependent tracking error. The result is aggressive flight up to 5 m/s with zero crashes in 500 randomized simulations.

Quadrotors can provide services such as infrastructure inspection and search-and-rescue, which require operating autonomously in cluttered environments. Autonomy is typically achieved with receding-horizon planning, where a short plan is executed while a new one is computed, because sensors receive limited information at any time. To ensure safety and prevent robot loss, plans must be verified as collision free despite uncertainty (e.g, tracking error). Existing spline-based planners dilate obstacles uniformly to compensate for uncertainty, which can be conservative. On the other hand, reachability-based planners can include trajectory-dependent uncertainty as a function of the planned trajectory. This work applies Reachability-based Trajectory Design (RTD) to plan quadrotor trajectories that are safe despite trajectory-dependent tracking error. This is achieved by using zonotopes in a novel way for online planning. Simulations show aggressive flight up to 5 m/s with zero crashes in 500 cluttered, randomized environments.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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