Papers
5
Total Citations
20
H-Index
3
About
Shubham Shukla is a robotics and autonomous systems researcher whose work spans robot motion planning, unmanned aerial vehicles (UAVs), and space robotics. His research is driven by a core challenge: enabling robots to navigate and operate intelligently in complex, unknown environments. Early in his career, Shukla made notable contributions to multi-robot path planning by applying bio-inspired optimization techniques, including Particle Swarm Optimization (PSO) and Cuckoo Search algorithms, to help robots efficiently navigate intricate obstacle-laden settings — work that collectively garnered over a dozen citations. Building on this foundation, he extended motion planning principles to UAVs, proposing a Lévy Flight-based probabilistic approach for navigating constricted environments such as tunnels and narrow passages. More recently, Shukla has ventured into the frontier of space robotics, contributing to the Hardware-in-the-Loop verification of Model Predictive Control for floating space robots designed for on-orbit servicing and debris removal missions. His work on holonomic drive robots further demonstrates his versatility across robotic platforms. With a growing citation record and an expanding research portfolio, Shukla represents an emerging voice in intelligent autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 5Dynamics and Control of a Mobile Kicking Robot2 citations · 2022