Papers

3

Total Citations

34

H-Index

3

About

Matthieu Jaccard is a robotics researcher whose work centers on motion planning and trajectory optimization for complex multi-arm robotic systems. His research addresses one of the most technically demanding challenges in industrial automation: enabling dual-arm and dual-gantry robotic systems to operate efficiently without colliding with one another while maintaining smooth, precise motion. Jaccard's most significant contribution is his development of B-spline-based motion planning frameworks for dual-arm Cartesian and gantry robots. His 2023 paper on collision-free and smooth motion planning, which has garnered 27 citations, introduced a method that achieves G2-continuity and low curvature profiles — qualities essential for high-speed, high-precision manufacturing applications. By elegantly parameterizing end-effector paths using multi-dimensional B-splines, his approach transforms a complex geometric and kinematic problem into a tractable optimization challenge. His follow-up 2025 work extends these principles to pick-and-place applications, incorporating feed rate profiling alongside path planning for more complete motion generation. With a growing citation record and a focused, technically rigorous body of work, Jaccard represents an emerging voice in industrial robotics research, particularly for applications demanding coordinated multi-arm autonomy.

Research Focus

Key Achievements

3
H-Index
3
Papers
34
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Collision-free and smooth motion planning of dual-arm Cartesian robot based on B-spline representation
27 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Applied Sciences and Arts of Southern Switzerland

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago