Nishant Sharma

University of Nebraska–Lincoln, Indraprastha Institute of Information Technology Delhi

Papers

Total Citations

H-Index

About

Nishant Sharma is a roboticist whose work focuses on path planning and software reliability for autonomous systems. His primary research areas include bio-inspired algorithms for robot navigation and impact analysis in robotic software architectures. Sharma’s most notable contribution is the development of novel path planning algorithms inspired by the classic bug algorithm. In his 2018 paper, "A virtual bug planning technique for 2D robot path planning" (9 citations), he introduced a method where simulated virtual bugs split upon sensing an obstacle, allowing for rapid path computation in cluttered environments. This work was preceded by "BugFlood: A bug inspired algorithm for efficient path planning in an obstacle rich environment" (2016, 7 citations), which demonstrated a fast, near-optimal approach to collision-free navigation. Beyond navigation, Sharma has also addressed the critical challenge of software evolution in robotics. His 2017 paper, "Rate impact analysis in robotic systems" (5 citations), provides a framework for tracing the effects of system updates on control and data flow, helping developers mitigate performance degradation. Through these contributions, Sharma has advanced both the theoretical and practical aspects of robotic autonomy, offering efficient solutions for real-time path planning and robust software maintenance.