Obstacle avoidance via B-spline parameterizations of flat trajectories

TL;DR

This paper introduces a novel approach for obstacle avoidance in multi-agent systems by combining differential flatness and B-spline parametrization to ensure continuous constraint validation and efficient trajectory planning.

Contribution

It proposes a new geometrical framework using B-splines and differential flatness for collision avoidance, enabling exact and sub-optimal solutions validated through simulations.

Findings

Constraints can be validated at all times using the proposed method.

The approach provides both exact and sub-optimal trajectory solutions.

Validated effectiveness through extensive simulations on aerial vehicle models.

Abstract

This paper considers the collision avoidance problem in a multi-agent multi-obstacle framework. The originality in solving this intensively studied problem resides in the proposed geometrical view combined with differential flatness for trajectory generation and B-splines for the flat output parametrization. Using some important properties of these theoretical tools we show that the constraints can be validated at all times. Exact and sub-optimal constructions of the collision avoidance optimization problem are provided. The results are validated through extensive simulations over standard autonomous aerial vehicle dynamics.