Papers
2
Total Citations
12
H-Index
2
About
Avijit Ashe is a robotics researcher whose work centers on autonomous mobile robotics, human-robot interaction, and intelligent motion planning. His research focuses on developing sophisticated control frameworks for person-following robots — systems designed to autonomously track and accompany humans through complex, dynamically changing environments. A central theme across his publications is the application of Model Predictive Control (MPC) to address some of the most demanding challenges in mobile robotics, including real-time target tracking, collision avoidance, and navigating occluded or cluttered spaces. His 2021 paper on maneuvering intersections and occlusions using MPC-based prioritized tracking for differential drive robots has garnered 8 citations, demonstrating growing recognition within the robotics community. His earlier 2020 work on dynamic target tracking and collision avoidance behavior further established his foundational contributions to robust person-following behavior in service robots, accumulating 4 citations. Together, these works highlight his commitment to bridging theoretical control strategies with practical robotic deployment. For students and researchers working at the intersection of autonomous navigation, service robotics, and human-robot collaboration, Avijit Ashe's contributions offer valuable insights into building reliable, real-world-ready robotic systems.
Research Focus
Key Achievements
Top Papers
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