Papers
9
Total Citations
340
H-Index
7
About
Yao Cai is a robotics researcher whose career has been defined by pioneering contributions to the control and motion planning of spherical mobile robots — a challenging class of nonholonomic systems with compelling applications in hostile and unmanned environments. Working extensively with the BHQ series of spherical robots developed at his laboratory, Cai has tackled some of the most difficult problems in the field, including trajectory tracking, path following, and stabilization of systems that resist conventional chained-form control transformations. His most cited work, "Path Tracking Control of a Spherical Mobile Robot" (2012, 99 citations), exemplifies his ability to bridge kinematic modeling with practical controller design. Across a prolific body of research, he has applied backstepping methods, neural network architectures including RBF networks, angular momentum conservation principles, and neurodynamics to advance spherical robot control — collectively accumulating over 340 citations. More recently, Cai has expanded his scope to broader mobile robotics challenges, integrating deep reinforcement learning with model predictive control for real-time collision-free navigation. His sustained focus on underactuated, nonholonomic systems has made him a foundational figure for researchers entering the field of unconventional mobile robot design and autonomous motion control.
Research Focus
Key Achievements
Top Papers
- 1Path tracking control of a spherical mobile robot99 citations · 2012
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- 4Neural Network Control for the Linear Motion of a Spherical Mobile Robot32 citations · 2011
- 5Motion control of spherical robot based on conservation of angular momentum29 citations · 2009
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- 9Trajectory Tracking of a Spherical Robot Based on an RBF Neural Network7 citations · 2011