Ibrahim Awwal

University of California, Berkeley

Papers

2

Total Citations

1,269

H-Index

2

About

Ibrahim Awwal is a leading figure in robotic motion planning, whose work has fundamentally advanced how robots navigate complex, obstacle-filled environments. His primary research focuses on trajectory optimization, collision avoidance, and sequential convex programming. Awwal’s major contribution is the development of a novel optimization-based framework that transforms the traditionally intractable problem of collision-free motion planning into a series of efficiently solvable convex subproblems. His landmark 2014 paper, “Motion planning with sequential convex optimization and convex collision checking,” has amassed over 840 citations, establishing it as a cornerstone of modern robotics. In this work, Awwal introduced a method that, like the renowned CHOMP algorithm, can refine naïve, collision-prone straight-line paths into smooth, locally optimal trajectories. His earlier 2013 paper, with over 429 citations, laid the groundwork by incorporating a hinge loss penalty for collisions into the optimization loop. Awwal’s approach is celebrated for its robustness and speed, enabling robots to find feasible paths in high-dimensional spaces where traditional sampling-based planners struggle. His contributions are essential reading for any student or researcher seeking to understand state-of-the-art motion planning.

Research Focus

Key Achievements

2
H-Index
2
Papers
1,269
Total Citations
635
Avg Citations/Paper
🏆 Most Cited Paper
Motion planning with sequential convex optimization and convex collision checking
840 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago