3 papers
cs.RO2026
Safe and Stable Neural Network Dynamical Systems for Robot Motion Planning
Allen Emmanuel Binny, Mahathi Anand, Hugo T. M. Kussaba +4
Learning safe and stable robot motions from demonstrations remains a challenge, especially in complex, nonlinear tasks involving dynamic, obstacle-rich environments. In this paper,…
eess.SY2025
Who Moved My Distribution? Conformal Prediction for Interactive Multi-Agent Systems
Allen Emmanuel Binny, Anushri Dixit
Uncertainty-aware prediction is essential for safe motion planning, especially when using learned models to forecast the behavior of surrounding agents. Conformal prediction is a s…
cs.RO2025
Scalable Learning of High-Dimensional Demonstrations with Composition of Linear Parameter Varying Dynamical Systems
Shreenabh Agrawal, Hugo T. M. Kussaba, Lingyun Chen +4
Learning from Demonstration (LfD) techniques enable robots to learn and generalize tasks from user demonstrations, eliminating the need for coding expertise among end-users. One es…