Papers
2
Total Citations
5
H-Index
2
About
Aneesh Sharma’s research focuses on the intersection of robotics, motion planning, and terrain-aware control, with a particular emphasis on enabling robots to operate safely and efficiently under physical constraints. His major contributions lie in developing algorithms that explicitly account for torque and energy limitations during manipulation and locomotion tasks. In his highly cited 2016 work, Sharma introduced a dynamics-based approach to incorporate torque constraints into manipulator planning under heavy loads, ensuring feasible trajectories when robots face steep inclines or lift substantial weight. He extended this line of inquiry in 2017 with experimental validation on skid-steered platforms, demonstrating how terrain difficulty should dynamically inform the trade-off between shortest-path and energy-optimal motion planning. Though his citation counts are modest—3 and 2 respectively—these papers represent foundational steps in bridging theoretical constraint modeling with real-world robotic deployment. Sharma’s work is particularly notable for its practical emphasis on field robotics, where ignoring torque or energy limits can lead to mission failure. His research offers valuable insights for students and engineers designing robots for agriculture, construction, or planetary exploration.
Research Focus
Key Achievements
Top Papers
- 1
- 2