Model Predictive Planner for UAV Navigation in Non-Convex Air Corridors
Abstract
This work presents a motion planning framework for UAV navigation in non-convex urban air corridors. The planner is based on a mixed-integer tracking model predictive control formulation that enforces corridor feasibility and dynamic consistency within a single optimization problem. To guarantee convergence to the target and mitigate the occurrence of local minima induced by non-convex geometry, a shortest-path-based offset cost with feasibility constraints is embedded directly into the planning...
Description / Details
This work presents a motion planning framework for UAV navigation in non-convex urban air corridors. The planner is based on a mixed-integer tracking model predictive control formulation that enforces corridor feasibility and dynamic consistency within a single optimization problem. To guarantee convergence to the target and mitigate the occurrence of local minima induced by non-convex geometry, a shortest-path-based offset cost with feasibility constraints is embedded directly into the planning problem. Numerical simulations show that the proposed formulation generates dynamically valid trajectories that satisfy the corridor constraints and converge to the target without relying on external global planning stages.
Source: arXiv:2607.24369v1 - http://arxiv.org/abs/2607.24369v1 PDF: https://arxiv.org/pdf/2607.24369v1 Original Link: http://arxiv.org/abs/2607.24369v1
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Jul 28, 2026
Robotics
Robotics
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