Jiyu Cheng

About

Jiyu Cheng is a robotics and artificial intelligence researcher whose work spans autonomous navigation, visual localization, and multi-robot systems. With a body of research that has collectively accumulated hundreds of citations, Cheng has established himself as a significant contributor to the challenge of enabling robots to operate reliably in complex, real-world environments. His most influential contributions address one of robotics' fundamental difficulties: localization and navigation in dynamic settings where moving objects violate the static-world assumptions underpinning many classical algorithms. His papers on sparse motion removal and dynamic region removal (2019–2020, combined 118 citations) offer robust solutions that substantially improve visual localization accuracy. Complementing this, his widely read surveys on autonomous navigation in human environments and mobile robot path planning provide the field with authoritative overviews of state-of-the-art techniques. Cheng has also pushed boundaries in multi-robot coordination, proposing the H2GNN hierarchical graph neural network framework for collaborative exploration, and in combinatorial optimization, applying deep reinforcement learning to industrial 3D bin packing problems (63 citations). His POMDP-based semantic object search pipeline further demonstrates his breadth across probabilistic reasoning and practical deployment. Together, these contributions make Cheng a versatile and impactful voice in modern autonomous systems research.

Research Focus

Key Achievements

Top Papers

1. 1
   Robust Visual Localization in Dynamic Environments Based on Sparse Motion Removal

   72 citations · 2019
2. 2
   Heuristics Integrated Deep Reinforcement Learning for Online 3D Bin Packing

   63 citations · 2023
3. 3
   Autonomous Navigation by Mobile Robots in Human Environments: A Survey

   58 citations · 2018
4. 4
   Efficient Object Search With Belief Road Map Using Mobile Robot

   49 citations · 2018
5. 5
   H2GNN: Hierarchical-Hops Graph Neural Networks for Multi-Robot Exploration in Unknown Environments

   48 citations · 2022
6. 6
   Improving Visual Localization Accuracy in Dynamic Environments Based on Dynamic Region Removal

   46 citations · 2020
7. 7
   Mobile Robot Path Planning in Dynamic Environments: A Survey

   43 citations · 2020
8. 8
   Safe and Robust Mobile Robot Navigation in Uneven Indoor Environments

   40 citations · 2019
9. 9
   A survey of autonomous robots and multi-robot navigation: Perception, planning and collaboration

   36 citations · 2024
10. 10
    Semantic-Aware Informative Path Planning for Efficient Object Search Using Mobile Robot

    36 citations · 2019

Key Collaborators

Contact & Links