Papers
9
Total Citations
145
H-Index
6
About
Kaushlendra Sharma is a leading researcher in multi-robot systems and autonomous navigation, with a primary focus on path planning, task scheduling, and cloud-based robotics. His most impactful work, "Coordination of multi-robot path planning for warehouse application using smart approach for identifying destinations" (42 citations), introduces intelligent coordination strategies that optimize robot movement in logistics environments. Sharma has made significant contributions to search and rescue operations, developing a real-time survivor detection system (28 citations) that addresses the critical challenge of locating humans in disaster debris after earthquakes, hurricanes, or explosions. His innovative application of nature-inspired algorithms, particularly the optimized cuckoo search with tournament selection (27 citations), has advanced robot path planning by improving efficiency and obstacle avoidance. Sharma also pioneered the PMW algorithm for cloud-based multi-robot task scheduling (17 citations), enabling autonomous task allocation in complex multi-robot environments. His work on early obstacle detection and snake model path planning further demonstrates his commitment to reducing computation time and traverse space. With over 145 total citations across his publications, Sharma's research directly impacts real-world applications in warehouse automation, disaster response, and autonomous robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Real-Time Survivor Detection System in SaR Missions Using Robots28 citations · 2022
- 3
- 4Cloud Based Multi-Robot Task Scheduling Using PMW Algorithm17 citations · 2023
- 5Path planning for robots: an elucidating draft11 citations · 2020
- 6
- 7Early Detection of Obstacle to Optimize the Robot Path Planning6 citations · 2022
- 8Reducing Traverse Space in Path Planning using Snake Model for Robots5 citations · 2019
- 9