Nikolay A. Atanasov
Vikas Dhiman
Shumon Koga
workshop (5251) deep learning (1092) robots (1015) icra (59) safe control (1) international conference on robotics and automation (1)
Guaranteeing safety is crucial for the effective deployment of robots. Control theory research has established techniques with theoretical safety and stability guarantees based on model predictive control, reference governor design, Hamilton-Jacobi reachability, control Lyapunov and barrier functions, and contraction theory. Similarly, formal methods techniques based on SMT solvers and hybrid system verification have been used to guarantee safety in systems. Existing techniques, however, predominantly assum
With recent progress in machine learning we can learn robot dynamics or environment models from sensory data. Gaussian Process regression and Koopman Operator theory have shown promise in estimating robot dynamics models. Deep neural network models have enabled impressive results in 3D reconstruction from visual data. Although empirically impressive, these machine learning techniques, however, do not provide guarantees for safety.
This workshop seeks to bring together experts from multiple communities – robotics, control theory and machine learning – and highlight the cutting-edge research in their intersection. We will feature talks from both the fields with an emphasis on safe robot control in uncertain environments.
Nikolay A. Atanasov
Vikas Dhiman
Shumon Koga