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cs.RO2026

MOCHA: Multi-Objective Co-Design using Hypernetwork Architectures

Varun Madabushi, Neil Janwani, Maegan Tucker

In this work, we present MOCHA, the first, to our knowledge, reinforcement learning based approach to computing a family of Pareto-optimal policies across the design space of a rob…

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 stable…

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…