Safe Navigation and Obstacle Avoidance Using Differentiable Optimization Based Control Barrier Functions

Understand

Control barrier functions (CBFs) have been widely applied to safety-critical robotic applications.

• However, the construction of control barrier functions for robotic systems remains a challenging task.
• Recently, collision detection using differentiable optimization has provided a way to compute the minimum uniform scaling factor that results in an intersection between two convex shapes and to also compute the Jacobian of the scaling factor.
• In this letter, we propose a framework that uses this scaling factor, with an offset, to systematically define a CBF for obstacle avoidance tasks.