Ruixiang
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Ruixiang
Ruixiang

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I am a Robotics Engineer with a focus on autonomous navigation of mobile robots. My areas of interest include sensing and motion planning for self-driving cars, general mobile robot planning, control and simulation, and real-time embedded systems. I was a PhD candidate in Mechanical Engineering at Worcester Polytechnic Institute (WPI) in the USA and worked in the Autonomy, Control, and Estimation Laboratory (ACEL) under supervision of Professor Raghvendra V. Cowlagi. I dropped out of the PhD program in early 2019 since I was not able to return to school for a prolonged period due to visa issue after an international travel.

  • Master of Science in Aerospace Engineering, WPI, 2019
  • PhD Candidate in Mechanical Engineering, WPI, 2016-18
  • Master of Science in Robotics Engineering, WPI, 2013
  • Bachelor of Engineering in Automation, NCEPU, 2011
Motion Prediction and Planning for Connected and Automated Vehicles
Many people anticipate 5G communication would help autonomous driving make a breakthrough and reach the next-level of autonomy. But how is V2X technology actually going to make a self-driving car safer and more efficient? What if majority of surrounding vehicles are still manually driven by human even though more and more of them are expected to be enhanced with communication capabilities? In this project, we studied existing/emerging vehicular communication technologies and investigated commonly available information that can be exchanged among vehicles. We tried to use probabilistic reachable set to predict potential occupancy by surrounding vehicles and evaluate collision risk within planning horizon of the ego (autonomous) vehicle. The goal is to selectively "listen to" vehicles that are relevant to ego vehicle's motion in order to reduce onboard computation as well as mitigating communication channel congestion in busy regions.
Path Repair and Trajecotry Optimization for Small Unmanned Aerial Vehicles
Small electric quadrotors have become commertially available for a wide range of applications, such as photography, construction site inspection and agriculture. Though these UAVs are suitable for cluttered environments by its size and manuverability, their applications are largely restricted to relatively open areas. Can we make them fly autonomously in places like warehouses, factories or densely populated urban neighbourhoods? In this project, we proposed a path repair algorithm for small UAVs equipped with FOV-limited onboard 3D sensor to efficiently navigate in large indoor environments where only a 2D map is available beforehand. The vehicle would try to take full advantage of information from the 2D map and actively look for "shortcuts" in the 3D space based on analysis with the map together with realtime sensor data.
DARPA Robotics Challenge Trials & Finals
The DARPA Robotics Challenge (DRC) was introduced after the Fukushima nuclear disaster happened in Japan, 2011. It's aimed at pushing the boundaries of technology and making life saving robotics systems available for future disasters. WPI's entry of the DRC started from the Virtual Robotics Challenge phase, in which we got the 2nd place and won an Atlas Robot built by Boston Dynamics. During the DRC Trials phase, we formed a collaborative team with CMU and successfully qualified as one of the finalists in December 2013. Our team WPI-CMU successfully finished the DRC Finals and ranked the 7th out of 23 competing teams from all over the world, in California, June 2015. Our development work invovled many aspects of robotics, such as scene segmentation and object detection, whole-body control of the humanoid robot, path and step planning, trajectory planning and control for manipulation, behavior management and human-robot interaction.
Self-driving Car (nuTonomy)Quadrotor Attitude Control
2D Mobile Robot SimulatorMedical Robot Simulation
Here are a few open-source packages I've been working on over the past a few years, together with some screenshots of planning-related algorithms implemented in the packages:
  • libgraph: C++ class templates for graph construction and search.
  • robotnav: A lightweight mobile navigation framework
  • imtoolkit: Immediate-mode UI/visualization toolkit for robotics software development
Lattice Generation
Probabilistic Occupancy Estimation
Minimum-snap Trajectory Generation
RRT Search
RRG Search
RRT* Search

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