Huaiyu Xiao — accepted AI-conference papers

2022

Towards a Hybrid-ASP Planning Approach With Adjoint Observation for Incomplete Task-Relevant Information

Shuo Yang, Xinjun Mao, Yuanzhou Xue, Huaiyu Xiao, Shuo Wang

RA-L 2022

In the real world, robot task plans may easily become invalid due to unexpected state dynamics, preventing the robot from accessing the complete task-relevant information. The possible occurrence of information incompleteness during robot plan execution expects the robot to sense the environment and

Cited by 1 Source ↗Scholar ↗

2021

Towards Adjoint Sensing and Acting Schemes and Interleaving Task Planning for Robust Robot Plan

Shuo Yang, Xinjun Mao, Shuo Wang, Huaiyu Xiao, Yuanzhou Xue

ICRA 2021poster

Robots operating in open environments expect to have robust plans to achieve tasks successfully under environment uncertainties. However, both partial observability and dynamics of environment states have significantly decreased the robustness of task achievement, making robot task planning much mor…

Cited by 2 Source ↗Scholar ↗