Yasir Saleem

University of Engineering and Technology Lahore

Papers

Total Citations

H-Index

About

Yasir Saleem is a robotics researcher whose work focuses on multi-agent systems, hierarchical decision-making, and intelligent control for autonomous robots. His key research areas include multi-robot coordination, reinforcement learning, and hardware implementation of robotic controllers. Saleem’s major contributions lie in developing scalable frameworks for robotic search teams operating in uncertain environments. In his 2016 and 2021 papers, each with 4 citations, he introduced hierarchical multi-agent architectures based on Markov decision processes and reinforcement learning, enabling robots to collaboratively search unknown areas while handling environmental uncertainty. These models address critical gaps in existing multi-agent systems by improving decision-making efficiency and adaptability. Additionally, his 2017 work on FPGA-based gait controllers for biped robots demonstrates his expertise in bridging theory and practice, using inverse kinematics and zero moment point algorithms to generate stable walking patterns. Though his citation counts are modest, Saleem’s research contributes foundational ideas to the growing field of autonomous multi-robot systems, offering practical solutions for search-and-rescue, exploration, and industrial automation. His interdisciplinary approach—combining AI, control theory, and hardware design—positions him as a promising researcher advancing the frontiers of intelligent robotics.