20 citations · 31 across the 8 of their papers we have counts for
7 papers · 1 filter
Guide-LLM: An Embodied LLM Agent and Text-Based Topological Map for Robotic Guidance of People with Visual Impairments
Sangmim Song, Sarath Kodagoda, Amal Gunatilake +3
Navigation presents a significant challenge for persons with visual impairments (PVI). While traditional aids such as white canes and guide dogs are invaluable, they fall short in…
DeepGoal: Learning to Drive with driving intention from Human Control Demonstration
Huifang Ma, Yue Wang, Rong Xiong +2
Recent research on automotive driving developed an efficient end-to-end learning mode that directly maps visual input to control commands. However, it models distinct driving varia…
Weakly-Supervised Road Affordances Inference and Learning in Scenes without Traffic Signs
Huifang Ma, Yue Wang, Rong Xiong +2
Road attributes understanding is extensively researched to support vehicle's action for autonomous driving, whereas current works mainly focus on urban road nets and rely much on t…
Real-Time 3D Profiling with RGB-D Mapping in Pipelines Using Stereo Camera Vision and Structured IR Laser Ring
Amal Gunatilake, Lasitha Piyathilaka, Sarath Kodagoda +2
This paper is focused on delivering a solution that can scan and reconstruct the 3D profile of a pipeline in real-time using a crawler robot. A structured infrared (IR) laser ring…
Towards navigation without precise localization: Weakly supervised learning of goal-directed navigation cost map
Huifang Ma, Yue Wang, Li Tang +2
Autonomous navigation based on precise localization has been widely developed in both academic research and practical applications. The high demand for localization accuracy has be…
Fast, On-board, Model-aided Visual-Inertial Odometry System for Quadrotor Micro Aerial Vehicles
Dinuka Abeywardena, Shoudong Huang, Ben Barnes +2
The main contribution of this paper is a high frequency, low-complexity, on-board visual-inertial odometry system for quadrotor micro air vehicles. The system consists of an extend…