320 citations · 963 across the 78 of their papers we have counts for
8 papers · 1 filter
DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration
Xiangcheng Hu, Xieyuanli Chen, Mingkai Jia +3
LiDAR point cloud registration is fundamental to robotic perception and navigation. In geometrically degenerate environments (e.g., corridors), registration becomes ill-conditioned…
Complete Gaussian Splats from a Single Image with Denoising Diffusion Models
Ziwei Liao, Mohamed Sayed, Steven L. Waslander +3
Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct…
OpenNav: Open-World Navigation with Multimodal Large Language Models
Mingfeng Yuan, Letian Wang, Steven L. Waslander
Pre-trained large language models (LLMs) have demonstrated strong common-sense reasoning abilities, making them promising for robotic navigation and planning tasks. However, despit…
aUToPath: Unified Planning and Control for Autonomous Vehicles in Urban Environments Using Hybrid Lattice and Free-Space Search
Tanmay P. Patel, Connor Wilson, Ellina R. Zhang +4
This paper presents aUToPath, a unified online framework for global path-planning and control to address the challenge of autonomous navigation in cluttered urban environments. A k…
Trends in Motion Prediction Toward Deployable and Generalizable Autonomy: A Revisit and Perspectives
Letian Wang, Marc-Antoine Lavoie, Sandro Papais +13
Motion prediction, recently popularized as world models, refers to the anticipation of future agent states or scene evolution, which is rooted in human cognition, bridging percepti…
Large Self-Supervised Models Bridge the Gap in Domain Adaptive Object Detection
Marc-Antoine Lavoie, Anas Mahmoud, Steven L. Waslander
The current state-of-the-art methods in domain adaptive object detection (DAOD) use Mean Teacher self-labelling, where a teacher model, directly derived as an exponential moving av…