Papers
44
Total Citations
522
H-Index
14
About
Leena Vachhani’s research lies at the intersection of robotics, control systems, and hardware-efficient computing, with a focus on autonomous navigation, multi-robot coordination, and surgical skill assessment. Her pioneering work on FPGA-based CORDIC implementations (42 citations) and control-law-driven generalized Voronoi diagram construction (38 citations) has enabled real-time, resource-constrained robotic exploration and obstacle avoidance. She has advanced multi-robot patrolling through deep reinforcement learning (27 citations) and decentralized graph exploration with collision avoidance (25 citations), addressing scalability and safety in dynamic environments. Her contributions to discrete-time sliding mode control for unicycle robots (23 citations) and motion planning for spherical robots (21 citations) demonstrate expertise in handling nonlinear dynamics and actuator constraints. Notably, her recent work on surgical instrument detection and tracking (34 citations) automates dataset labeling for surgical skill assessment, bridging robotics and healthcare. With over 270 total citations, Vachhani’s hardware-efficient algorithms and control strategies have significantly impacted autonomous systems, from search-and-rescue robots to surgical training, making her a leading figure in practical, deployable robotics solutions.
Research Focus
Key Achievements
Top Papers
- 1Efficient FPGA Realization of CORDIC With Application to Robotic Exploration42 citations · 2009
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10Pose estimation for an autonomous vehicle using monocular vision18 citations · 2017