Amit Bhatia

Rice University, University of Illinois Urbana-Champaign

Papers

Total Citations

541

H-Index

About

Amit Bhatia is a leading researcher in robotics and motion planning, with a focus on integrating complex, high-level temporal goals into autonomous navigation. His work addresses the critical challenge of enabling mobile robots to not only reach a destination but to do so while satisfying intricate, time-sensitive specifications. Bhatia’s most influential contribution is a multi-layered, synergistic framework that bridges the gap between low-level geometric planning and high-level temporal logic, allowing for the synthesis of provably correct motion plans. His seminal 2010 paper, "Sampling-based motion planning with temporal goals," which has garnered 243 citations, laid the foundation for this approach. This work, along with his 2011 article "Motion Planning with Complex Goals" (121 citations), demonstrates how to decompose complex temporal tasks into simpler sub-problems, solved efficiently using sampling-based algorithms. Bhatia’s research also extends to hybrid systems, as seen in his 2004 work on reachability analysis (122 citations) and his 2010 paper on hybrid dynamics (55 citations), showcasing his ability to handle systems with both continuous and discrete behaviors. His contributions are essential for the next generation of autonomous systems, from self-driving cars to robotic assistants, that must operate safely and intelligently in dynamic environments.