ROAM Lab (Robotics, Optimization, and Motion)
ROAM Lab at University of Notre Dame develops fundamental control strategies for quadruped robots using Model Hierarchy Predictive Control (MHPC). Research focuses on endowing robots with agility and robustness to navigate challenging terrains and environments.
Notable achievements
Cascaded-Fidelity Model Predictive Control for quadrupeds, terrain-adaptive locomotion
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
Parallel Differentiable Reachability for Learning and Planning with Certified Neural Dynamics and Controllers
Keyi Shen, Glen Chou
2026
Trajectory tracking control for 6WID/4WIS UGV via nonlinear sliding mode-model predictive control with adaptive following steering and dynamic-static constraints
Shengyang Lu, Guanpeng Chen, Lijing Zhao +2 more
Robotics and Autonomous Systems · 2026
Graph-Based Modeling, Control, and Optimization for Multi-Domain and Multi-Timescale Energy Systems
Joseph M. Pisani, Christopher T. Aksland, Philip M. Renkert +7 more
2026
Optimal Dispatch of Connected and Autonomous Electric Vehicles to Enhance Short-Term Grid Flexibility in Smart Cities
Nikolas Sacchi, Giacomo Basile, Silvia Siri +3 more
2026
Dynamic robotic cloth folding with efficient Koopman operator-based model predictive control
Edoardo Caldarelli, Franco Coltraro, Adrià Colomé +2 more
2026
Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations
Jonathan Spieler, Angel Villar-Corrales, Sven Behnke
2026