Max Robotics — Global Service Robot Directory + US Certification

About

Shaunak D. Bopardikar is a researcher whose work spans robotics, autonomous systems, and control theory, with particular focus on robotic perception, path planning under uncertainty, and observability-aware control. His most recognized contribution, "Active Exploration using Trajectory Optimization for Robotic Grasping in the Presence of Occlusions" (2015, 49 citations), introduced a trajectory optimization framework enabling robots to intelligently navigate unstructured environments and grasp occluded objects using RGB-D sensing — a practically significant advance for real-world robotic manipulation. Beyond perception, Bopardikar has made meaningful strides in uncertainty-aware motion planning. His MM-RRT* algorithm addresses localization uncertainty by minimizing worst-case state estimation error during path planning, while complementary work on observability-aware target tracking and control barrier functions demonstrates his sustained interest in ensuring robots maintain reliable situational awareness using only range measurements. His research on attack-resilient path planning using dynamic game theory further highlights his range, addressing security challenges for autonomous vehicles operating in adversarial environments. More recently, he has explored underwater optical communication for mobile robots, reflecting a breadth rarely seen in a single research portfolio. With contributions cited across robotics, control systems, and cybersecurity communities, Bopardikar represents an increasingly important voice at the intersection of perception, planning, and resilient autonomy.