Mohamed Bilal Shakeel
Birla Institute of Technology and Science, Pilani - Dubai Campus
Papers
1
Total Citations
7
H-Index
1
About
Mohamed Bilal Shakeel is a researcher at the forefront of bio-inspired robotics and intelligent control systems, with a focus on enabling autonomous manipulation in unstructured environments. His most-cited work, "A Vision-Based Bio-Inspired Reinforcement Learning Algorithms for Manipulator Obstacle Avoidance" (2022, 7 citations), tackles a critical challenge in industrial robotics: path planning for manipulators in unknown, dynamic settings. By integrating vision-based perception with reinforcement learning, Shakeel’s approach overcomes the limitations of traditional algorithms that rely on predefined maps, allowing robots to adapt in real time. This contribution is particularly significant for advancing automation in complex manufacturing and service robotics. Shakeel’s research elegantly bridges computational intelligence and biological inspiration, offering scalable solutions for obstacle avoidance without exhaustive environmental modeling. His work has already garnered attention for its practical implications, and he continues to explore how learning-based methods can enhance robotic autonomy. For students and researchers, Shakeel’s profile exemplifies how combining reinforcement learning with bio-inspired design can push the boundaries of what robotic manipulators can achieve in the real world.
Research Focus
Key Achievements
Top Papers
- 1