3 papers
cs.RO2026
MO-Playground: Massively Parallelized Multi-Objective Reinforcement Learning for Robotics
Neil Janwani, Ellen Novoseller, Vernon J. Lawhern +1
Multi-objective reinforcement learning (MORL) is a powerful tool to learn Pareto-optimal policy families across conflicting objectives. However, unlike traditional RL algorithms, e…
cs.RO2025
NaviGait: Navigating Dynamically Feasible Gait Libraries using Deep Reinforcement Learning
Neil Janwani, Varun Madabushi, Maegan Tucker
Reinforcement learning (RL) has emerged as a powerful method to learn robust control policies for bipedal locomotion. Yet, it can be difficult to tune desired robot behaviors due t…
cs.RO2023
A Learning-Based Framework for Safe Human-Robot Collaboration with Multiple Backup Control Barrier Functions
Neil C. Janwani, Ersin Daş, Thomas Touma +3
Ensuring robot safety in complex environments is a difficult task due to actuation limits, such as torque bounds. This paper presents a safety-critical control framework that lever…