11 papers
Principles of Robot Autonomy
Daniele Gammelli, Joseph Lorenzetti, Katie Luo +2
Autonomous robots are moving rapidly from research labs into everyday life - on roads, in the air, in warehouses, and in space. Robot autonomy is no longer solely an academic pursu…
Semantic Constraint Synthesis for Adaptive Trajectory Optimization via Large Language Models
Eleanor Brosius, Yuji Takubo, Daniele Gammelli +2
Trajectory optimization is a critical component for enabling safe and reliable autonomous operations in space exploration. As space missions increase in frequency, complexity, and…
Multi-Timescale Model Predictive Control for Slow-Fast Systems
Lukas Schroth, Daniel Morton, Amon Lahr +3
Model Predictive Control (MPC) has established itself as the primary methodology for constrained control, enabling autonomy across diverse applications. While model fidelity is cru…
Graph Neural Model Predictive Control for High-Dimensional Systems
Patrick Benito Eberhard, Luis Pabon, Daniele Gammelli +5
The control of high-dimensional systems, such as soft robots, requires models that faithfully capture complex dynamics while remaining computationally tractable. This work presents…
Reproducibility in the Control of Autonomous Mobility-on-Demand Systems
Xinling Li, Meshal Alharbi, Daniele Gammelli +7
Autonomous Mobility-on-Demand (AMoD) systems, powered by advances in robotics, control, and Machine Learning (ML), offer a promising paradigm for future urban transportation. AMoD…
Vision Foundation Model Embedding-Based Semantic Anomaly Detection
Max Peter Ronecker, Matthew Foutter, Amine Elhafsi +4
Semantic anomalies are contextually invalid or unusual combinations of familiar visual elements that can cause undefined behavior and failures in system-level reasoning for autonom…