Muhammad Salman

About

Muhammad Salman is a dynamic researcher whose work spans robotics, autonomous systems, and intelligent control — fields that are rapidly reshaping modern engineering and human-machine interaction. His most influential contribution, a 2021 study on Mel-spectrogram and deep CNN-based bio-sonar processing for UAVs (19 citations), demonstrates his ability to bridge biological inspiration with cutting-edge machine learning, enabling drones to estimate forest leaf density through bat-like echolocation. His prolific output in robot manipulator control is equally impressive, with multiple high-impact papers exploring robust trajectory tracking, impedance control, and perturbation observer-based methods — collectively accumulating dozens of citations across robotics communities. Notably, his work on Super Twisting Sliding Mode Control and force/torque-based impedance control reflects a sophisticated grasp of nonlinear control theory applied to real-world challenges, including assistive robotics for paraplegics and nuclear power plant maintenance. His sensor-less collision detection research further highlights his commitment to practical, cost-effective robotic solutions. With contributions spanning path planning, dynamic modelling, and teleoperation, Salman has established himself as a versatile and impactful voice in modern robotics and autonomous systems research.

Research Focus

Key Achievements

Top Papers

1. 1
   Mel-spectrogram and Deep CNN Based Representation Learning from Bio-Sonar Implementation on UAVs

   19 citations · 2021
2. 2
   Robust Control Design for Accurate Trajectory Tracking of Multi-Degree-of-Freedom Robot Manipulator in Virtual Simulator

   12 citations · 2022
3. 3
   Perturbation Observer-Based Obstacle Detection and Its Avoidance Using Artificial Potential Field in the Unstructured Environment

   11 citations · 2023
4. 4
   Super Twisting Sliding Mode Control-Based Impedance Control for Robot Arm End-Effector Force Tracking

   6 citations · 2022
5. 5
   Force/Torque-Based Impedance Control With Perturbation Observer—Toward High Payload System Robust Trajectory Tracking

   6 citations · 2022
6. 6
   Real Time Voronoi-like Path Planning Using Flow Field and A

   4 citations · 2020
7. 7
   Dynamics Analysis and Control of 5 DOF Robot Manipulator

   3 citations · 2021
8. 8
   Sensor-less Obstacle Collision Detection for Robot Manipulator

   3 citations · 2022
9. 9
   Super Twisting Sliding Mode Control-Based Impedance Control for Teleoperated Virtual Robot Arm End-Effector Force Tracking

   2 citations · 2022

Key Collaborators

Contact & Links