My research interest lies in algorithmic robotics and robot motion planning. Specifically I am using explanation-failure planning approaches to tackle challenging robotic manipulation tasks in unstructured and uncertain environment. One project I am working on is to finding safe and effective picking paths for robot arms in a setup where the target object is occluded by other surrounding objects or has only partial view. Pose estimation methods have been integrated into the planning pipeline and the planning problem is modeled as the stochastic version of Minimal Constraint Removal (MCR) problem. My research work bridges the gap between perception and motion planning, which are the two big pieces in the field of robotics. For more details of this research project, you can see this project website and its corresponding dataset.
I am also exploring research opportunities in multi-object rearrangement problems in dual-arm robotic system, where explanation-failure planning tools can be powerful to solve non-monotone instances. The rearrangement problems have broad applications in robotics and can be highly challenging if the space for the robot arms to operate is highly confined and constrained.
Besides being committed to performing high-quality research, I have also great enthusiasm in teaching. I have been selected as the course instructor for the summer course Introduction to Artificial Intelligence for two consecutive years (2019, 2020). From 2017-2019, I had also been working as a teaching assistant for multiple courses.
Prior to my Ph.D. in Rutgers, I earned my Master Degree in Mechanical Engineering from Columbia University in the city of New York, where I was working with Dr. Peter Allen on several robot car navigation tasks. I earned my Bachelor Degree in Vehicle Engineering from Nanjing University of Aeronautics and Astronautics, Nanjing, China.
For more information, feel free to contact me at rui [dot] wang26 [at] rutgers [dot] edu