- 09/2014-04/2017 Master of Science, School of Computing Science, Simon Fraser University
- 09/2015-08/2016 Graduate Certificate in Science and Technology Commercialization, Beedie School of Business, Simon Fraser University
Study frameworks, perspective and techniques for research scientists and engineers to contribute to new product development and commercialization in industry.
SFU Science & Technology Scholarship
- 09/2010-06/2014 Bachelor of Engineering, School of Electronic and Informaition Engineering, Beijing Jiaotong University
Cumulative GPA: 87/100, Major GPA: 90/100, Ranking: 21/220 2011-2013 Dean’s List
(15%) Scholarship for Scientific Innovation Excellence 2013 (1%), Scholarship for Community Work Excellence 2012 (3%)
- Optimal Robot Selection by Gaze Direction in Multi-Human Multi-Robot Interaction
L. Zhang, R. Vaughan
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), Korea, October 2016. (PDF)
- Optimal Gaze-Based Robot Selection in Multi-Human Multi-Robot Interaction
L. Zhang, R. Vaughan
Human-Robot Interaction Pioneers Workshop at the 2016 ACM/IEEE International Conference on Human-Robot Interaction (HRI 2016 Workshop), Christchurch, New Zealand, March 2016 (PDF).
- Orbiting a Moving Target with Multi-Robot Collaborative Visual SLAM
J. Perron*, R. Huang*, J. Thomas, L. Zhang, P. Tan, R. Vaughan
Workshop on Multi-View Geometry in Robotics (MVIGRO) at the 2015 Robotics: Science and System Conference (RSS 2015 Workshop), Rome, Italy, July 2015 (PDF)
- A Gaze-based Attention System for Multi-human Multi-robot Interaction
Master thesis (PDF)
This project presents a computer vision based system for interaction between multiple humans and multiple robots. Each human can “select” (obtain the undivided attention of) a robot by simply looking directly at it. This extends previous work whereby a single human can select one or more robots from a population. Each robot optimally assigns human identities to tracked faces in its camera view using a local Hungarian algorithm. Then the system finds the global optimal allocation of robot-to-human selections using a second, centralized, Hungarian algorithm. This is the first demonstration of optimal many-to-many robot-selection HRI.
Cooperative Behaviour for Model Training with Autonomous Mobile Robots
In order to gain the benefits of supervised learning techniques without requiring a human to construct a labeled dataset, we have developed a behavior for a pair of mobile robots to train a visual classifier on their own. This autonomous approach takes advantage of the rote nature of dataset creation to allow machines to replace humans with little appreciable loss of performance. A specific implementation of this behavior was written for Chatterbox robots, whose automatically-built dataset was compared to human-constructed ones.
Orbiting a Moving Target with Multi-Robot Collaborative Visual SLAM
Towards autonomous 3D modelling of moving targets, we present a system where multiple ground-based robots cooperate to localize, follow and scan from all sides a movingtarget. Each robot has a single camera as its only sensor, and they perform collaborative visual SLAM (CoSLAM). We present a simple robot controller that maintains the visual constraints of CoSLAM while orbiting a moving target so as to observe it from all sides. Real-world experiments demonstrate that multiple ground robots can successfully track and scan a moving target. (video)
The third generation of inspiRED humanoid robot, a 50cm humanoid robot. Its controller is a low-cost but powerful single-board Linux computer Odroid-XU4 and we use ROS and Open-CV with it. It walks, barely.
Mobile robot controlled by Raspberry Pi, equipped with a camera, two stereo speakers, a bumper and four IR distance sensors.
The second generation of inspiRED humanoid robot, a child-size (80 cm) humanoid robot. Its controller is a low-cost but powerful single-board Linux computer Odroid-U3 and we use ROS and Open-CV with it.
InspiRED is a LEGO-like 3D-printable humanoid robot platform featured with highly-customized components. Its controller is a low-cost but powerful single-board Linux computer Odroid-U3 and we use ROS and Open-CV with it. A large number of commonly used electronic equipments including RC servos, camera, HDMI-display, IR sensor, IMU, speaker, microphone, LED, PS2 controller and etc. are supported. We participated in the robotics startup competition, “Ogopogo’s Lair” and won funding support from NCFRN.
Initial is a 40-cm humanoid robot. It’s used for testing of running ROS on single board computer, Odriod U3, which talks to a low level controller board for controlling servo motors via serial port. It is also equipped with an HD camera, and the video stream can be transported to the laptop via wifi.
It was for Challenge Cup University Students Science and Technology Competition. I was the project leader and covered most of the programming and algorithms designing work. We designed and made the Intelligent Navigation And Tracking Robot in one year. And we ended up with winning the first prize in Beijing and was the only team in my university that gaining the qualification for national final 2013, where we won the second prize.
I developed a quadcopter based on STM32 since 2013.11. A WLAN Model is attached to its CPU so that it can be controlled by a mobile phone via WLAN. And it is equipped with a video camera to recognize and track certain patterns.
I developed a rover based on ARM7 in 2013.02. It is controlled by LPC2148, and its position can be detected by using Zigbee equipments which is connected to a laptop which can display it.
I studied the basic algorithms and take the programming races on Codeforces and other online platforms. I officially became a member of BJTU ACM/ICPC team in 2012. And I, together with my two teamates, took the Asian zone qualified of 37th ACM/ICPC in 2012, winning a bronze medal finally. (Solved problems collection are in the Algorithm category of this blog.)
TECO Green Tech International Contest
TECO Green Technology International Contest is a contest on environmentally-friendly technology organized by TECO Technology Foundation in Taiwan in 2013. Our team’s project, Indoor Localization and Navigation based on Zibee was enrolled in the Internation Final, together with Tsinghua University, Tokio University, Singapore Nayang University, Moscow State University and etcetra. (more about this)
- Teaching Assistant for CMPT 125/127 – Computing Laboratory
I was the TA for CMPT 125/127 in Simon Fraser University in 2014 fall and 2015 fall. This class teaches the basics of programming in C and C++, with an emphasis on program design and testing. The standard UNIX command-line build and version control tools are used.
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