Tal Regev

Technion – Israel Institute of Technology

Papers

Total Citations

H-Index

About

Tal Regev is a robotics researcher specializing in autonomous multi-robot systems, with a particular focus on decentralized planning under uncertainty. His work addresses one of the most challenging problems in modern robotics: enabling teams of robots to operate collaboratively and intelligently in unknown, unstructured environments without relying on centralized coordination. Regev's most significant contribution lies in the development of novel belief space planning frameworks for multi-robot systems. His 2016 paper, which has garnered 20 citations, introduced an innovative approach to decentralized multi-robot belief space planning in high-dimensional state spaces, leveraging sampling-based motion planning paradigms to allow robots to efficiently reassess and adapt their planned paths in real time. This work was further refined in a 2017 follow-up study, accumulating an additional 11 citations, which enhanced the framework through improved identification and re-evaluation of impacted paths. By addressing the computational challenges inherent in operating across high-dimensional state spaces, Regev's research has meaningfully advanced the field of probabilistic robotics and autonomous navigation. His contributions are particularly relevant to applications in search-and-rescue, exploration, and other scenarios where robust, decentralized robot coordination is critical.