SC3BF: Shifted Collision Cone Control Barrier Function for Dynamic Obstacle Avoidance

📅 2026-10-06
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🤖 AI Summary
This study addresses the excessive conservatism of traditional velocity-space Control Barrier Function (CBF) collision cones, which reject all relative velocities directed toward obstacles. To overcome this limitation, we propose a shifted collision cone CBF method that introduces a state-dependent allowance mechanism, enabling robots to dynamically approach obstacles based on distance and velocity. We theoretically prove the existence of a non-zero safety margin and derive its closed-form solution without requiring assumptions on minimum forward velocity or clearance margins. Integrated with quadratic programming optimization and a kinematic bicycle model, experiments in multi-moving-obstacle scenarios demonstrate that the proposed method significantly improves goal-reaching rates compared to baseline approaches while reducing nominal control modifications by approximately 50%.
📝 Abstract
The collision cone used by velocity-space control barrier functions is conservative: it rejects every relative velocity aimed into an obstacle, however slow. We propose the \emph{shifted collision-cone CBF} (SC3BF), which adds a state-dependent \emph{allowance} to the cone condition, so the robot may approach the obstacle at a rate that grows with distance and with its own speed. SC3BF is enforced by an ordinary quadratic program, and its safe set is forward invariant under bounded inputs without a minimum forward speed or a clearance margin. We prove that a nonzero allowance preserving safety always exists, and derive one in closed form. Against three velocity-space baselines on a kinematic bicycle among up to $100$ moving obstacles, SC3BF reaches the goal more often and modifies the nominal input less than half as much.
Problem

Research questions and friction points this paper is trying to address.

Dynamic Obstacle Avoidance
Control Barrier Function
Collision Cone
Velocity Space
Innovation

Methods, ideas, or system contributions that make the work stand out.

Control Barrier Function
Collision Cone
Dynamic Obstacle Avoidance
Quadratic Programming
Shifted Collision-Cone
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A
Amin Kashiri
Department of Electrical and Computer Engineering at Northeastern University, Boston, MA
Yasin Yazıcıoğlu
Yasin Yazıcıoğlu
Assistant Professor, Northeastern University
ControlRoboticsMultiagent Systems