Vikas Thapa

University of Petroleum and Energy Studies

Papers

Total Citations

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About

Vikas Thapa is a robotics researcher whose work focuses on advancing autonomous navigation and localization for mobile robots in complex indoor environments. His most influential contribution, "Obstacle avoidance for mobile robot using RGB-D camera" (2017, 6 citations), demonstrates how integrating the Kinect as a vision sensor with the Robot Operating System (ROS) enables effective real-time obstacle detection and avoidance in cluttered settings. This research addresses a fundamental challenge in mobile robotics—safe autonomous movement—by leveraging affordable depth-sensing technology. In his earlier work, "Investigation on optimized relative localization of a mobile robot using regression analysis" (2016, 3 citations), Thapa tackles the critical issue of accurate position estimation. He improves upon traditional odometry by applying regression analysis to optimize kinematic parameters for differential drive robots, enhancing relative localization without expensive sensors. Together, these studies highlight Thapa’s commitment to practical, cost-effective solutions for robot perception and control. His research is valuable for students and engineers developing autonomous systems for warehouses, homes, or hospitals, offering accessible methods to improve robot reliability and safety in real-world applications.