Tingxiang Fan

Orcid: 0009-0005-6314-2596

According to our database¹, Tingxiang Fan authored at least 24 papers between 2018 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

S<sup>2</sup> MAT : Simultaneous and Self-Reinforced Mapping and Tracking in Dynamic Urban Scenarios.

[BibT_eX]

[DOI]

J. Field Robotics, January, 2026

2023

SMAT: A Self-Reinforcing Framework for Simultaneous Mapping and Tracking in Unbounded Urban Environments.

[BibT_eX]

[DOI]

CoRR, 2023

Design, Sensing and Control of Service Robotic System for Intelligent Navigation and Operation in Internet Data Centers.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023

2022

DiffSRL: Learning Dynamical State Representation for Deformable Object Manipulation With Differentiable Simulation.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2022

DynamicFilter: an Online Dynamic Objects Removal Framework for Highly Dynamic Environments.

[BibT_eX]

[DOI]

Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021

An Efficient and Responsive Robot Motion Controller for Safe Human-Robot Collaboration.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

VR-ORCA: Variable Responsibility Optimal Reciprocal Collision Avoidance.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

DiffSRL: Learning Dynamic-aware State Representation for Deformable Object Control with Differentiable Simulator.

[BibT_eX]

[DOI]

CoRR, 2021

Autonomous Social Distancing in Urban Environments Using a Quadruped Robot.

[BibT_eX]

[DOI]

IEEE Access, 2021

2020

A Two-Stage Reinforcement Learning Approach for Multi-UAV Collision Avoidance Under Imperfect Sensing.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2020

Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios.

[BibT_eX]

[DOI]

Int. J. Robotics Res., 2020

Autonomous Social Distancing in Urban Environments using a Quadruped Robot.

[BibT_eX]

[DOI]

CoRR, 2020

Crowd-Driven Mapping, Localization and Planning.

[BibT_eX]

[DOI]

Proceedings of the Experimental Robotics - The 17th International Symposium, 2020

DeepMNavigate: Deep Reinforced Multi-Robot Navigation Unifying Local & Global Collision Avoidance.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

An Actor-Critic Approach for Legible Robot Motion Planner.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Learning Resilient Behaviors for Navigation Under Uncertainty.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Modeling 3D Shapes by Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Safe Navigation With Human Instructions in Complex Scenes.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Getting Robots Unfrozen and Unlost in Dense Pedestrian Crowds.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2019

Learning Resilient Behaviors for Navigation Under Uncertainty Environments.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Fully Distributed Multi-Robot Collision Avoidance via Deep Reinforcement Learning for Safe and Efficient Navigation in Complex Scenarios.

[BibT_eX]

[DOI]

CoRR, 2018

CrowdMove: Autonomous Mapless Navigation in Crowded Scenarios.

[BibT_eX]

[DOI]

CoRR, 2018

Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Intervention Aided Reinforcement Learning for Safe and Practical Policy Optimization in Navigation.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Tingxiang Fan

Timeline

Legend:

Links

On csauthors.net:

Bibliography

Loading...