2 citations · 2 across the 8 of their papers we have counts for
9 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…
Minimalistic Autonomous Stack for High-Speed Time-Trial Racing
Mahmoud Ali, Hassan Jardali, Youwei Yu +2
Autonomous racing has seen significant advancements, driven by competitions such as the Indy Autonomous Challenge (IAC) and the Abu Dhabi Autonomous Racing League (A2RL). However,…
Chance-Constrained Sampling-Based MPC for Collision Avoidance in Uncertain Dynamic Environments
Ihab S. Mohamed, Mahmoud Ali, Lantao Liu
Navigating safely in dynamic and uncertain environments is challenging due to uncertainties in perception and motion. This letter presents the Chance-Constrained Unscented Model Pr…
Visual-Geometry GP-based Navigable Space for Autonomous Navigation
Mahmoud Ali, Durgkant Pushp, Zheng Chen +1
Autonomous navigation in unknown environments is challenging and demands the consideration of both geometric and semantic information in order to parse the navigability of the envi…
Gaussian Process-based Traversability Analysis for Terrain Mapless Navigation
Abe Leininger, Mahmoud Ali, Hassan Jardali +1
Efficient navigation through uneven terrain remains a challenging endeavor for autonomous robots. We propose a new geometric-based uneven terrain mapless navigation framework combi…
Autonomous Mapless Navigation on Uneven Terrains
Hassan Jardali, Mahmoud Ali, Lantao Liu
We propose a new method for autonomous navigation in uneven terrains by utilizing a sparse Gaussian Process (SGP) based local perception model. The SGP local perception model is tr…
GP-guided MPPI for Efficient Navigation in Complex Unknown Cluttered Environments
Ihab S. Mohamed, Mahmoud Ali, Lantao Liu
Robotic navigation in unknown, cluttered environments with limited sensing capabilities poses significant challenges in robotics. Local trajectory optimization methods, such as Mod…
GP-Frontier for Local Mapless Navigation
Mahmoud Ali, Lantao Liu
We propose a new frontier concept called the Gaussian Process Frontier (GP-Frontier) that can be used to locally navigate a robot towards a goal without building a map. The GP-Fron…