6 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…
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…
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…
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…
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…
Laguerre-Gauss Preprocessing: Line Profiles as Image Features for Aerial Images Classification
Alejandro Murillo-González, José David Ortega Pabón, Juan Guillermo Paniagua +1
An image preprocessing methodology based on Fourier analysis together with the Laguerre-Gauss Spatial Filter is proposed. This is an alternative to obtain features from aerial imag…