Shashank Sharma
Augsburg University, KUKA (Germany), Indian Institute of Technology Kanpur
Papers
6
Total Citations
54
H-Index
3
About
Shashank Sharma is a leading researcher in mobile manipulation, a field at the intersection of robotics, control theory, and human-robot interaction. His work focuses on solving the complex analytical challenges of coordinating mobile platforms with robotic arms to achieve seamless, "true" mobile manipulation. Sharma’s major contributions include developing unified closed-form inverse kinematics solutions for highly redundant systems, such as the KUKA youBot, which have become foundational references in the field. His 2012 paper on this topic has garnered 24 citations, while his 2016 work on multi-task redundancy resolution at velocity level has been cited 19 times, underscoring their impact on industrial and service robotics. Sharma has also advanced sensor fusion techniques, using Kalman filters to integrate visual-inertial data for precise end-effector tracking, and explored human-robot collaboration through hand-guidance systems that optimize effective mass for improved operator experience. His research addresses practical industrial needs, from redundancy resolution to obstacle avoidance, making his work highly relevant for engineers and researchers aiming to enhance the versatility and safety of mobile manipulators in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1Unified Closed Form Inverse Kinematics for the KUKA youBot24 citations · 2012
- 2
- 3Kalman Filter Based Sensor Fusion for a Mobile Manipulator4 citations · 2019
- 4
- 5
- 6When is an obstacle a perfect obstacle2 citations · 1998