1 citations · 1 across the 11 of their papers we have counts for
11 papers
ForestSim: A Synthetic Benchmark for Intelligent Vehicle Perception in Unstructured Forest Environments
Pragat Wagle, Zheng Chen, Lantao Liu
Robust scene understanding is essential for intelligent vehicles operating in natural, unstructured environments. While semantic segmentation datasets for structured urban driving…
AFRDA: Attentive Feature Refinement for Domain Adaptive Semantic Segmentation
Md. Al-Masrur Khan, Durgakant Pushp, Lantao Liu
In Unsupervised Domain Adaptive Semantic Segmentation (UDA-SS), a model is trained on labeled source domain data (e.g., synthetic images) and adapted to an unlabeled target domain…
Adaptive Diffusion Terrain Generator for Autonomous Uneven Terrain Navigation
Youwei Yu, Junhong Xu, Lantao Liu
Model-free reinforcement learning has emerged as a powerful method for developing robust robot control policies capable of navigating through complex and unstructured terrains. The…
C^2DA: Contrastive and Context-aware Domain Adaptive Semantic Segmentation
Md. Al-Masrur Khan, Zheng Chen, Lantao Liu
Unsupervised domain adaptive semantic segmentation (UDA-SS) aims to train a model on the source domain data (e.g., synthetic) and adapt the model to predict target domain data (e.g…
Context-Generative Default Policy for Bounded Rational Agent
Durgakant Pushp, Junhong Xu, Zheng Chen +1
Bounded rational agents often make decisions by evaluating a finite selection of choices, typically derived from a reference point termed the default policy,' based on previous…
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…
Boundary-Aware Value Function Generation for Safe Stochastic Motion Planning
Junhong Xu, Kai Yin, Jason M. Gregory +2
Navigation safety is critical for many autonomous systems such as self-driving vehicles in an urban environment. It requires an explicit consideration of boundary constraints that…
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…
PlanarNeRF: Online Learning of Planar Primitives with Neural Radiance Fields
Zheng Chen, Qingan Yan, Huangying Zhan +7
Identifying spatially complete planar primitives from visual data is a crucial task in computer vision. Prior methods are largely restricted to either 2D segment recovery or simpli…
POVNav: A Pareto-Optimal Mapless Visual Navigator
Durgakant Pushp, Zheng Chen, Chaomin Luo +2
Mapless navigation has emerged as a promising approach for enabling autonomous robots to navigate in environments where pre-existing maps may be inaccurate, outdated, or unavailabl…