collaborators

8 papers

eess.SY2026

Comparison of Non-Deterministic Nonlinear Systems

Shivam Bajaj, Varun S. Madabushi, Maegan Tucker +1

We characterize a notion of system comparison, termed as -similarity, for non-deterministic nonlinear systems. Building on a similar notion recently proposed for stabl…

cs.LG2026

Active Query Synthesis for Preference Learning

Namrata Nadagouda, Nauman Ahad, Maegan Tucker +1

Efficient learning of user preferences is crucial for many modern decision making systems but typically requires costly labeled data. Active learning reduces this cost, yet standar…

eess.SY2026

Differentiable Invariant Sets for Hybrid Limit Cycles with Application to Legged Robots

Varun Madabushi, Akash Harapanahalli, Samuel Coogan +1

For hybrid systems exhibiting periodic behavior, analyzing the invariant set containing the limit cycle is a natural way to study the robustness of the closed-loop system. However,…

eess.SY2026

Finite-Step Invariant Sets for Hybrid Systems with Probabilistic Guarantees

Varun Madabushi, Elizabeth Dietrich, Hanna Krasowski +1

Poincare return maps are a fundamental tool for analyzing periodic orbits in hybrid dynamical systems, including legged locomotion, power electronics, and other cyber-physical syst…

cs.RO2026

Kinodynamic Motion Retargeting for Humanoid Locomotion via Multi-Contact Whole-Body Trajectory Optimization

Xiaoyu Zhang, Steven Haener, Varun Madabushi +1

We present the KinoDynamic Motion Retargeting (KDMR) framework, a novel approach for humanoid locomotion that models the retargeting process as a multi-contact, whole-body trajecto…

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…