Papers
10
Total Citations
117
H-Index
5
About
Muhammad Shahab Alam is a robotics researcher whose work spans precision agriculture, autonomous navigation, and assistive robotics. His key contributions include developing TobSet, a specialized image dataset for tobacco crop and weed discrimination that enables vision-based selective spraying by agricultural robots—a critical advancement for reducing agrochemical use. In mobile robotics, Alam has pioneered path planning algorithms using Particle Swarm Optimization, demonstrating effective navigation through environments cluttered with non-convex obstacles and danger sources, with his 2020 paper on PSO-based path planning accumulating 28 citations. His applied robotics work includes designing a compliant robotic gripper for orange harvesting and a wearable walk-assist device with adaptive compliance control, both addressing real-world challenges in agriculture and healthcare. Alam has also contributed to bionic limb design and multi-robot systems for warehouse logistics using reinforcement learning. With over 100 total citations across his publications, his research demonstrates a consistent focus on bridging optimization algorithms, computer vision, and mechanical design to create practical robotic solutions for agriculture, mobility assistance, and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4Design and Compliance Control of a Robotic Gripper for Orange Harvesting14 citations · 2019
- 5Design and Adaptive Compliance Control of a Wearable Walk Assist Device10 citations · 2023
- 6
- 7Design and Control of a Bionic Leg4 citations · 2023
- 8
- 9
- 10