5 papers
HJ-SafeDMP: Hamilton-Jacobi Reachability-Guided Dynamic Movement Primitives for Provably Safe Robot Motion
Siddhanth Ramesh, Ravi Prakash
Robots deployed in safety-critical environments must execute motions that are simultaneously robust to disturbances and provably safe from collisions. Dynamic Movement Primitives (…
V-OCBF: Learning Safety Filters from Offline Data via Value-Guided Offline Control Barrier Functions
Mumuksh Tayal, Manan Tayal, Aditya Singh +2
Ensuring safety in autonomous systems requires controllers that aim to satisfy state-wise constraints without relying on online interaction.While existing Safe Offline RL methods t…
SafeDMPs: Integrating Formal Safety with DMPs for Adaptive HRI
Soumyodipta Nath, Pranav Tiwari, Ravi Prakash
Robots operating in human-centric environments must be both robust to disturbances and provably safe from collisions. Achieving these properties simultaneously and efficiently rema…
RISE: Robust Imitation through Stochastic Encoding
Mumuksh Tayal, Manan Tayal, Ravi Prakash
Ensuring safety in robotic systems remains a fundamental challenge, especially when deploying offline policy-learning methods such as imitation learning in dynamic environments. Tr…
CPED-NCBFs: A Conformal Prediction for Expert Demonstration-based Neural Control Barrier Functions
Sumeadh MS, Kevin Dsouza, Ravi Prakash
Among the promising approaches to enforce safety in control systems, learning Control Barrier Functions (CBFs) from expert demonstrations has emerged as an effective strategy. Howe…