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Control barrier functions (CBFs) provide a simple yet effective way for safecontrol synthesis. Recently, work has been done using differentiableoptimization (diffOpt) based methods to systematically construct CBFs forstatic obstacle avoidance tasks between geometric shapes. In this work, weextend the application of diffOpt CBFs to perform dynamic obstacle avoidancetasks. We show that by using the time-varying CBF (TVCBF) formulation, we canperform obstacle avoidance for dynamic geometric obstacles. Additionally, weshow how to extend the TVCBF constraint to consider measurement noise andactuation limits. To demonstrate the efficacy of our proposed approach, wefirst compare its performance with a model predictive control based method anda circular CBF based method on a simulated dynamic obstacle avoidance task.Then, we demonstrate the performance of our proposed approach in experimentalstudies using a 7-degree-of-freedom Franka Research 3 robotic manipulator.

Differentiable Optimization Based Time-Varying Control Barrier Functions for Dynamic Obstacle Avoidance