- Strategic Advisor
- Distinguished Professor
- Institution: Queensland University of Technology (QUT)
Bio: Peter is a robotics researcher and educator. He is the distinguished professor of robotic vision at Queensland University of Technology and was director of the ARC Centre of Excellence for Robotic Vision (2014-2020). His research is concerned with robotic perception using vision and force, dynamics and control, and the application of robots to mining, agriculture and environmental monitoring. He created widely used open-source software for teaching and research, wrote the bestselling textbook “Robotics, Vision, and Control”, created several MOOCs and the Robot Academy, and has won national and international recognition for teaching including 2017 Australian University Teacher of the Year.
Peter is the Chief Scientist of Dorabot (Shenzhen) and on the advisory boards of Emesent and LYRO. He is a fellow of the IEEE, the Australian Academy of Technology and Engineering, the Australian Academy of Science; former editor-in-chief of the IEEE Robotics & Automation magazine; founding editor of the Journal of Field Robotics; founding multi-media editor and executive editorial board member of the International Journal of Robotics Research; member of the editorial advisory board of the Springer Tracts on Advanced Robotics series; recipient of the Qantas/Rolls-Royce and Australian Engineering Excellence awards; and has held visiting positions at Oxford, University of Illinois, Carnegie-Mellon University and University of Pennsylvania. Prior to QUT, he founded and led CSIRO’s Autonomous Systems Laboratory (2004-2009). He received his undergraduate and master’s degrees in electrical engineering and PhD in mechanical and manufacturing engineering, all from the University of Melbourne.
Research Expertise: Peter is interested in how robots can use sensory information such as vision, force and touch to increase the breadth and reliability of tasks they do in our everyday world. He has a particular interest in the sense of vision, and human hand-eye coordination is wonderful motivating example that highlights the stark difference between human and current robot capability. Some specific topics of interest include:
- The use of visual information for controlling robot motion, a technique known as visual servoing.
- Very wide field-of-view cameras based on fisheye lens and lens/mirror (catadioptric) optical systems.
- Optical flow, how images from a moving robot can be used to infer the world’s 3D structure and the robot’s motion
- Computer architectures for implementing computer vision algorithms in real time
- Stereo vision, using information from one or more cameras to create the 3D world structure.
- The combination arm and mobile robots to create mobile manipulation systems
- Vision processing within networks of cameras.
- Super-fast hand-eye coordination