Muhammad Suhail Saleem

Carnegie Mellon University

Papers

3

Total Citations

16

H-Index

2

About

Muhammad Suhail Saleem is a robotics researcher whose work focuses on advancing robot manipulation in highly cluttered and constrained environments. His primary research areas include motion planning, physics-based simulation, and non-prehensile manipulation, with a particular emphasis on enabling robots to navigate complex, real-world scenes without requiring perfect object rearrangement. Saleem’s major contributions lie in developing algorithms that integrate heuristic search with optimization-based primitives, allowing high-dimensional manipulators—such as a 21-degree-of-freedom snake-like robot—to plan paths through tight spaces like gas turbine interiors for inspection tasks. His work on planning with selective physics-based simulation demonstrates how robots can reason about and execute actions that involve pushing objects aside, rather than meticulously clearing a path, making manipulation more efficient and practical. With his most-cited paper garnering 10 citations, Saleem’s research is gaining traction for its innovative approach to contact-rich interactions. His notable achievement includes the development of adaptive motion primitives that leverage physics to handle movable obstacles, a critical step toward deploying robots in unstructured human environments like cluttered kitchens or industrial sites.

Research Focus

Key Achievements

2
H-Index
3
Papers
16
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Search-based Path Planning for a High Dimensional Manipulator in Cluttered Environments Using Optimization-based Primitives
10 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago