85 citations · 166 across the 15 of their papers we have counts for
15 papers
Robot Planning and Situation Handling with Active Perception
Austine Oloo, Zainab Altaweel, Yohei Hayamizu +9
Current robots are capable of computing plans to accomplish complex tasks. However, real-world environments are inherently open and dynamic, and unforeseen situations frequently ar…
DKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planning
Xiaohan Zhang, Zainab Altaweel, Yohei Hayamizu +6
Vision-language models (VLMs) have been applied to robot task planning problems, where the robot receives a task in natural language and generates plans based on visual inputs. Whi…
Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning
Xiaohan Zhang, Yifeng Zhu, Yan Ding +4
In existing task and motion planning (TAMP) research, it is a common assumption that experts manually specify the state space for task-level planning. A well-developed state space…
Integrating Action Knowledge and LLMs for Task Planning and Situation Handling in Open Worlds
Yan Ding, Xiaohan Zhang, Saeid Amiri +5
Task planning systems have been developed to help robots use human knowledge (about actions) to complete long-horizon tasks. Most of them have been developed for "closed worlds" wh…
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang +4
Large language models (LLMs) have demonstrated remarkable zero-shot generalization abilities: state-of-the-art chatbots can provide plausible answers to many common questions that…
Grounding Classical Task Planners via Vision-Language Models
Xiaohan Zhang, Yan Ding, Saeid Amiri +4
Classical planning systems have shown great advances in utilizing rule-based human knowledge to compute accurate plans for service robots, but they face challenges due to the stron…
Task and Motion Planning with Large Language Models for Object Rearrangement
Yan Ding, Xiaohan Zhang, Chris Paxton +1
Multi-object rearrangement is a crucial skill for service robots, and commonsense reasoning is frequently needed in this process. However, achieving commonsense arrangements requir…
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…
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…
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…
Learning to Guide Human Attention on Mobile Telepresence Robots with 360 Vision
Kishan Chandan, Jack Albertson, Xiaohan Zhang +3
Mobile telepresence robots (MTRs) allow people to navigate and interact with a remote environment that is in a place other than the person's true location. Thanks to the recent adv…
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…