SOURCE-LINKED INTELLIGENCE

Battery-Aware Predictive Trajectory Planning and Control for Multirotors Under Disturbances

arXiv · AI, language, vision and robotics · article · Sep 10, 2026 · UTC

This paper presents a battery-aware predictive trajectory-planning and control framework for multirotors operating under spatially localized disturbances. Candidate trajectories are evaluated through closed-loop vehicle--motor--battery propagation, allowing disturbance-induced control demand, electrical energy, battery evolution, and terminal-voltage-dependent actuator capability to enter the planning process. % A reduced-order battery model is numerically benchmarked against an independently implemented Simscape equivalent-circuit reference, with a power NRMSE of $0.64\%$ and a cumulative-ene

Read original source ↗ Open in workspace

recordType: paper
region: Global

Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-10T20:24:14.000Z

First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.