I am an Applied Scientist Co-op at Amazon Robotics and a Robotics PhD candidate at Rutgers University, working with Professor Jingjin Yu. As a fifth-year Robotics Ph.D. with a Mathematics bachelor's degree, my research focuses on Task and Motion Planning. And During my research projects, I acquired a diverse range of experience in robotics, including perception, deep learning, and utilizing physics engines such as Isaac Gym and Pybullet. I also built various real-world robot systems. I'm actively looking for Robotics/AI full-time positions in 2024. Email: kg627 [AT] scarletmail.rutgers.edu |
IROS 2023 Finalist of Best RoboCup Paper Award. (Top 6\% among accepted papers) Issued by: IROS in October 2023
Gold Award of China Undergrad. Math. Contest in Modeling in Anhui Province (1/65 in USTC) Issued by: China Society for Industrial and Applied Mathematics in 2017
Reinforcement Learning Specialization. Issued by: Coursera in July 2023
Outstanding Graduates Issued by: University of Science and Technology of China in June 2019
Outstanding Student Scholarship (2015-2016) (2017-2018) Issued by: University of Science and Technology of China in 2016, 2018
Programming Languages: Python, Matlab, C++
Tools: Git, ROS, PyBullet, Gazebo, OpenCV, PyTorch, Gurobi, Drake, Isaac Gym
[Summitted to IROS 2024] Toward Holistic Planning and Control Optimization for Dual-Arm Rearrangement. [video] Co-authored by Zihe Ye, Duo Zhang, Jingjin Yu |
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[IJRR] Minimizing running buffers for tabletop object rearrangement: Complexity, fast algorithms, and applications. Co-authored by Baichuan Huang, Si Wei Feng, Jingjin Yu |
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[IROS 2023] Effectively Rearranging Heterogeneous Objects on Cluttered Tabletops. (Finalist of Best RoboCup Paper Award.) Co-authored by Justin Yu, Tanay Sandeep Punjabi, Jingjin Yu |
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[IROS 2022] Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement. Supervised by Prof. Jingjin Yu |
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[RSS 2021] On Minimizing the Number of Running Buffers for Tabletop Rearrangement. [project page] [video] [paper] [codes] Co-authored by Si Wei Feng, Jingjin Yu |
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Camera Calibration Software Measuring Perception Accuracy of RealSense Cameras. Collaboration with Justin Yu. |
[IROS 2023] Optimal and Stable Multi-Layer Object Rearrangement on a Tabletop. Co-authored by Andy Xu, Si Wei Feng, Jingjin Yu |
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[ICRA 2022] Fast High-Quality Tabletop Rearrangement in Bounded Workspace. Co-authored by Darren Lau, Baichuan Huang, Kostas E. Bekris, Jingjin Yu |
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[IROS 2021] Capacitated Vehicle Routing with Target Geometric Constraints. Supervised by Prof. Jingjin Yu |
K. Gao, S. W. Feng, B. Huang and J. Yu. Minimizing Running Buffers for Tabletop Object Rearrangement: Complexity, Fast Algorithms, and Applications. submitted to The International Journal of Robotics Research (IJRR).
K. Gao, J. Yu, T. S. Punjabi, and J. Yu. ``Effectively Rearranging Heterogeneous Objects on Cluttered Tabletops.’’ 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023) (Finalist of Best RoboCup Paper Award.).
Andy Xu*, K. Gao *, S. W. Feng*, and J. Yu. ``Optimal and Stable Multi-Layer Object Rearrangement on a Tabletop.’’ 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023).
K. Gao, and J. Yu. “On the Utility of Buffers in Pick-n-Swap Based Lattice Rearrangement.” 2023 IEEE International Conference on Robotics and Automation (ICRA 2023).
K. Gao and J. Yu. “Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement.” 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022).
K. Gao, D. Lau, B. Huang, K. E. Bekris and J. Yu. “Fast High-Quality Tabletop Rearrangement in Bounded Workspace.” 2022 IEEE International Conference on Robotics and Automation (ICRA 2022).
K. Gao and J. Yu. “Capacitated Vehicle Routing with Target Geometric Constraints.” 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021).
K. Gao, S. W. Feng, and J Yu. “On Minimizing the Number of Running Buffers for Tabletop Rearrangement.” 2021 Robotics: Science and Systems (RSS 2021).
R. Wang*, K. Gao *, D. Nakhimovich*, J. Yu, and K. E. Bekris. “Uniform Object Rearrangement: From Complete Monotone Primitives to Efficient Non-Monotone Informed Search.” 2021 IEEE International Conference on Robotics and Automation (ICRA 2021).
E. R. Vieira, K. Gao, D. Nakhimovich, J. Yu and K. E. Bekris. “Effective and Robust Non-Prehensile Manipulation via Persistent Homology Guided Monte-Carlo Tree Search” the 18th International Symposium on Experimental Robotics (ISER 2023).
E. R. Vieira, D. Nakhimovich, K. Gao, R. Wang, J. Yu and K. E. Bekris. “Persistent Homology for Effective Non-Prehensile Manipulation” 2022 IEEE International Conference on Robotics and Automation (ICRA 2022).
R. Wang, K. Gao, J. Yu, and K. E. Bekris. “Lazy Rearrangement Planning in Confined Spaces” the 32nd International Conference on Automated Planning and Scheduling (ICAPS 2022).
S. W. Feng, K. Gao, J. Gong, and J. Yu. “Sensor Placement for Globally Optimal Coverage of 3D-Embedded Surfaces.” 2021 IEEE International Conference on Robotics and Automation (ICRA 2021).
S. W. Feng, S. D. Han, K. Gao, and J. Yu. “Efficient Algorithms for Optimal Perimeter Guarding.” 2019 Robotics: Science and Systems (RSS 2019).
K. Gao *, Z. Ye*, D. Zhang*, B. Huang, and J. Yu “Toward Holistic Planning and Control Optimization for Dual-Arm Rearrangement.” Submitted to IROS 2024.
H. Chang, K. Gao, K. Boyalakuntla, A. Lee, B. Huang, H. U. Kumar, J. Yu, and A. Boularias “LGMCTS: Language-Guided Monte-Carlo Tree Search for Executable Semantic Object Rearrangement.” Submitted to IROS 2024.