Peter Gaskell

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About

Peter Gaskell is a leading figure in scalable robotics education and multi-robot systems, whose work bridges the gap between classroom instruction and real-world deployment. His most influential contribution is the **MBot platform**, a low-cost, modular mobile robot ecosystem that has trained over **1,400 students** at the University of Michigan and partner institutions since 2014. This platform, detailed in his 2024 paper (6 citations), enables hands-on learning in autonomous navigation at unprecedented scale, making advanced robotics accessible to undergraduates. Gaskell’s research also tackles a fundamental challenge in multi-robot experimentation: the fidelity-versus-scale tradeoff. In his 2018 work on **mixed-reality calibration** (2 citations), he developed a method to blend real and simulated robots, allowing researchers to test large teams with high physical fidelity—a critical advance for fields like swarm robotics and cooperative manipulation. By combining educational innovation with practical experimental tools, Gaskell has shaped how robotics is both taught and researched, empowering the next generation of engineers to build and test complex multi-robot systems.