1 citations · 1 across the 1 of their papers we have counts for
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Robotic Table Wiping via Reinforcement Learning and Whole-body Trajectory Optimization
Thomas Lew, Sumeet Singh, Mario Prats +11
We propose a framework to enable multipurpose assistive mobile robots to autonomously wipe tables to clean spills and crumbs. This problem is challenging, as it requires planning w…
GLAD: Grounded Layered Autonomous Driving for Complex Service Tasks
Yan Ding, Cheng Cui, Xiaohan Zhang +1
Given the current point-to-point navigation capabilities of autonomous vehicles, researchers are looking into complex service requests that require the vehicles to visit multiple p…
Visually Grounded Task and Motion Planning for Mobile Manipulation
Xiaohan Zhang, Yifeng Zhu, Yan Ding +3
Task and motion planning (TAMP) algorithms aim to help robots achieve task-level goals, while maintaining motion-level feasibility. This paper focuses on TAMP domains that involve…
Learning to Ground Objects for Robot Task and Motion Planning
Yan Ding, Xiaohan Zhang, Xingyue Zhan +1
Task and motion planning (TAMP) algorithms have been developed to help robots plan behaviors in discrete and continuous spaces. Robots face complex real-world scenarios, where it i…
Planning Multimodal Exploratory Actions for Online Robot Attribute Learning
Xiaohan Zhang, Jivko Sinapov, Shiqi Zhang
Robots frequently need to perceive object attributes, such as "red," "heavy," and "empty," using multimodal exploratory actions, such as "look," "lift," and "shake." Robot attribut…
Task-Motion Planning for Safe and Efficient Urban Driving
Yan Ding, Xiaohan Zhang, Xingyue Zhan +1
Autonomous vehicles need to plan at the task level to compute a sequence of symbolic actions, such as merging left and turning right, to fulfill people's service requests, where ef…