Real-Time B-Spline Path Planning for Vision-Based Collision Avoidance

Jen-Jui Liu, Curtis P. Evans, and Randal W. Beard

Peer Reviewed

Abstract:	In this paper, we present a novel approach to real-time collision avoidance and path planning for unmanned aerial vehicles (UAVs) using basic camera inputs. Our system predicts the future trajectories of nearby flying objects and computes a feasible path to avoid collisions while maintaining progress toward a target destination. Unlike traditional radar-based methods, our solution requires only two parameters from the visual feed—bearing and pixel size—allowing for lightweight, real-time obstacle detection and avoidance. This approach benefits UAVs operating in shared airspaces with manned aircraft, where rapid, autonomous decision-making is essential for safety. Preliminary results show that our system can efficiently compute avoidance maneuvers and plan routes in real-time, even in dynamic environments. Index Terms—Path Planning, B-Spline, Real-Time, Sense and Avoid (SAA)
Published in:	2025 IEEE/ION Position, Location and Navigation Symposium (PLANS) April 28 - 1, 2025 Salt Lake Marriott Downtown at City Creek Salt Lake City, UT
Pages:	1307 - 1318
Cite this article:	Liu, Jen-Jui, Evans, Curtis P., Beard, Randal W., "Real-Time B-Spline Path Planning for Vision-Based Collision Avoidance," 2025 IEEE/ION Position, Location and Navigation Symposium (PLANS), Salt Lake City, UT, April 2025, pp. 1307-1318.
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