Graeme Best

Graeme Best is a Lecturer in robotics at the University of Technology Sydney's School of Mechanical and Mechatronic Engineering within the Faculty of Engineering and Information Technology. He joined UTS in April 2022 after working as a Postdoctoral Scholar at Oregon State University from 2018 to 2022, where he collaborated with Carnegie Mellon University and University of Washington on projects funded by DARPA, ONR, NSF, and NAVFAC.

Dr. Best completed his PhD titled "Planning Algorithms for Multi-Robot Active Perception" at the University of Sydney's Australian Centre for Field Robotics. His educational background includes a BE (Electrical and Computer Systems) and BSc (Computer Science) from Monash University, both completed in 2014.

His research focuses on developing fundamental algorithms for multi-robot systems, with particular emphasis on active perception, where robots plan their motion to obtain high-value observations. His work spans from theoretical algorithm development to full-scale system demonstrations across diverse environments including subterranean spaces, marine settings, precision agriculture, and planetary exploration. He has pioneered approaches such as decentralized Monte Carlo tree search, self-organizing maps for active perception, and spatiotemporal optimal stopping to address challenges like online planning, decentralized coordination, long planning horizons, and unreliable communication.

Dr. Best's publication record shows a consistent trajectory of high-impact research in top robotics venues, with recent work focusing on behavior trees for intent communication, multi-room exploration, and resilient multi-sensor systems. His publications demonstrate strong interdisciplinary connections between theoretical computer science, control theory, and practical field robotics applications.

• Google Research Scholar Program Award (2023)
• DARPA Subterranean Challenge: Winner for the Tunnel Circuit (2019)
• DARPA Subterranean Challenge: Second Place for the Urban Circuit (2022)
• IEEE ICRA Best Paper Award on Multi-Robot Systems (2021)
• RSS Best Systems Paper Award, Finalist (2022)

Dr. Best actively contributes to the robotics community through editorial roles at major conferences including IEEE ICRA, IROS, and MRS. He currently serves as Program Director for UTS's undergraduate Mechatronics major and teaches courses related to robotics software and algorithms. His funded research includes projects like the Multi-Robot Mission Control System for Maritime Autonomous Systems and the Online Behaviour Tree Synthesis for Adaptive Multi-Agent Coordination project funded by Google.

He leads the UTS Motorsports Autonomous Vehicle team and supervises capstone projects, demonstrating his commitment to translating research into practical student experiences. His work on the DARPA Subterranean Challenge, where his team won the "Most Sectors Explored" award, exemplifies his ability to bridge theoretical research with real-world field applications.