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Reachability-Aware Time Scaling for Path Tracking

arXiv:2604.004396.5h-index: 12
AI Analysis

This work addresses path tracking challenges for robotic systems with bounded acceleration, but it is incremental as it builds on existing reachability-guided QP trackers.

The paper tackles the problem of tracking waypoint paths with sharp turns for a planar double-integrator system by developing a reachability-aware time scaling method that ensures acceleration limits are not exceeded, resulting in improved path tracking performance.

This paper studies tracking of collision-free waypoint paths produced by an offline planner for a planar double-integrator system with bounded speed and acceleration. Because sampling-based planners must route around obstacles, the resulting waypoint paths can contain sharp turns and high-curvature regions, so one-step reachability under acceleration limits becomes critical even when the path geometry is collision-free. We build on a pure-pursuit-style, reachability-guided quadratic-program (QP) tracker with a one-step acceleration margin. Offline, we evaluate this margin along a spline fitted to the waypoint path and update a scalar speed-scaling profile so that the required one-step acceleration remains below the available bound. Online, the same look-ahead tracking structure is used to track the scaled reference.

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