Jonathan Binney

University of Southern California, Embedded Systems (United States), VTT Technical Research Centre of Finland

Papers

Total Citations

167

H-Index

About

Jonathan Binney is a robotics researcher whose work spans informative path planning, robotic manipulation, and accessible robotics education. His most influential contribution is a graph-based algorithm for optimizing waypoints to monitor spatiotemporal phenomena, which explicitly handles time-dependent sampling and leverages submodular objective functions—a foundational approach for environmental monitoring with mobile robots (116 citations). Binney also advanced dexterous manipulation by developing methods to learn task error models for kinematic forward models, enabling robots to perform precise grasping even when visual servoing is occluded (34 citations). Beyond algorithmic contributions, he has been instrumental in the ROS ecosystem, addressing the challenge of managing complex, multi-component robot software systems through capabilities-based frameworks (11 citations). Demonstrating a commitment to broadening participation in robotics, Binney co-developed the "Just Add Wheels" approach, which repurposes commodity laptop hardware—including built-in sensors—to create affordable, accessible platforms for K–12 and undergraduate AI and robotics education (6 citations). His work uniquely combines theoretical rigor in planning and manipulation with practical, scalable solutions for both professional and educational robotics.