5 papers
Adaptive Smooth Tchebycheff Attention for Multi-Objective Policy Optimization
Alejandro Murillo-Gonzalez, Mahmoud Ali, Lantao Liu
Multi-objective reinforcement learning in robotic domains requires balancing complex, non-convex trade-offs between conflicting objectives. While linear scalarization methods provi…
Situationally-Aware Dynamics Learning
Alejandro Murillo-Gonzalez, Lantao Liu
Autonomous robots operating in complex, unstructured environments face significant challenges due to latent, unobserved factors that obscure their understanding of both their inter…
From Zero to High-Speed Racing: An Autonomous Racing Stack
Hassan Jardali, Durgakant Pushp, Youwei Yu +9
High-speed, head-to-head autonomous racing presents substantial technical and logistical challenges, including precise localization, rapid perception, dynamic planning, and real-ti…
Action Flow Matching for Continual Robot Learning
Alejandro Murillo-Gonzalez, Lantao Liu
Continual learning in robotics seeks systems that can constantly adapt to changing environments and tasks, mirroring human adaptability. A key challenge is refining dynamics models…
Learning Causal Structure Distributions for Robust Planning
Alejandro Murillo-Gonzalez, Junhong Xu, Lantao Liu
Structural causal models describe how the components of a robotic system interact. They provide both structural and functional information about the relationships that are present…