activity
20202026
most citedLLM+P: Empowering Large Language Models with Optimal Planning Proficiency

85 citations · 166 across the 15 of their papers we have counts for

collaborators
Showing 2022Show all

5 papers · 1 filter

cs.RO2022★ 1 cited

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…

cs.RO2022★ 1 cited

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…

cs.RO2022★ 3 cited

Robot Task Planning and Situation Handling in Open Worlds

Yan Ding, Xiaohan Zhang, Saeid Amiri +4

Automated task planning algorithms have been developed to help robots complete complex tasks that require multiple actions. Most of those algorithms have been developed for "closed…

cs.RO2022

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…

cs.RO2022

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…