Bishwajit Sharma

Centre for Artificial Intelligence and Robotics

Papers

Total Citations

H-Index

About

Bishwajit Sharma is a robotics researcher whose work focuses on autonomous indoor navigation, particularly the challenging problem of multi-floor robotic mobility. His primary research areas include staircase navigation, visual object detection, and sensor-based autonomous exploration for indoor robotic platforms. Sharma’s major contribution lies in bridging the gap between floor exploration and staircase climbing—two traditionally separate tasks in indoor robotics. His 2018 paper on autonomous staircase navigation systems (5 citations) and his 2019 work on computing optimal start-of-stair positions (5 citations) together provide a foundational framework for robots to seamlessly navigate between floors using onboard sensors. These contributions address critical issues in real-world deployment, such as determining where to begin climbing and integrating visual detection for obstacle avoidance. His 2018 paper on visual object detection (2 citations) further supports robust indoor perception. Though his citation counts are modest, Sharma’s work represents an important step toward fully autonomous multi-floor robotic systems, with potential applications in service robots, inspection, and search-and-rescue operations. His research demonstrates a practical, systems-level approach to solving complex navigation challenges.