Papers
3
Total Citations
33
H-Index
3
About
Reda Guernane is a robotics researcher whose work centers on motion planning and path optimization for robotic manipulators. His primary contributions lie in developing algorithms that generate safer, more efficient trajectories for industrial robots operating in cluttered environments. Guernane’s most influential paper, “Generating optimized paths for motion planning” (2011), has garnered 16 citations and introduces methods for producing execution-optimized paths while maintaining obstacle clearance. His earlier work, “A smoothing strategy for PRM paths application to six-axes MOTOMAN SV3X manipulator” (2005), with 12 citations, presents a novel strategy for refining probabilistic roadmap (PRM) paths using the SBL (single-query bidirectional probabilistic algorithm with lazy collision checking) technique, specifically applied to a six-axis industrial robot. In “An Algorithm for Generating Safe and Execution-Optimized Paths” (2009), Guernane further advanced the field by combining multiple-query PRM with a Lazy A* algorithm and weighted L∞ norm to extract optimized paths. His research has practical implications for manufacturing and automation, demonstrating how theoretical motion planning can be adapted for real-world robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Generating optimized paths for motion planning16 citations · 2011
- 2
- 3An Algorithm for Generating Safe and Execution-Optimized Paths5 citations · 2009