Safe Diffusion Policies for Robot Learning
Investigating inference-time safety mechanisms for diffusion policies in long-horizon robot decision-making, with a PyTorch framework spanning navigation and manipulation.
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1 min read
Constrained Policy Optimization via Sampling-Based Weight-Space Projection
Safety-critical learning requires policies that improve performance without leaving the safe operating regime. We study constrained policy learning where model parameters must …
Sampling-Based Constrained Policy Optimization
Proposed a sampling-based weight-space projection framework for enforcing safety constraints during policy updates.
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1 min read
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
Guaranteeing constraint satisfaction is a challenging problem in imitation learning (IL), especially when the task involves operating at the handling limits of the system. While …
Safe Imitation Learning at Handling Limits
Designed a constraint-aware imitation learning framework incorporating an actor-critic structure for explicit safety modeling.
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1 min read