Julien Bidot

Örebro University

Papers

3

Total Citations

202

H-Index

3

About

Julien Bidot is a leading researcher in robotic autonomy, whose work bridges the critical gap between high-level task planning and low-level geometric reasoning. His primary research areas include combined task and motion planning (CTAMP), constraint-based reasoning, and manipulation for humanoid robotic systems. Bidot’s major contribution is the development of a constraint-based framework that efficiently integrates symbolic task planning with geometric feasibility checks, enabling robots to solve complex, kinematically constrained problems. His seminal 2014 paper on this approach has garnered over 110 citations, establishing it as a foundational reference in the field. He further advanced the state of the art with his work on geometric backtracking (2015, 66 citations), which allows planners to recover from infeasible geometric configurations without restarting the entire planning process. Bidot’s earlier research on combining task and path planning for a humanoid two-arm system (2012, 26 citations) demonstrated practical applications in dexterous manipulation. His work is notable for its elegant integration of causal and geometric reasoning, providing a robust framework that has inspired subsequent research in autonomous robotics and continues to influence how robots reason about and interact with their physical environments.

Research Focus

Key Achievements

3
H-Index
3
Papers
202
Total Citations
67
Avg Citations/Paper
🏆 Most Cited Paper
Efficiently combining task and motion planning using geometric constraints
110 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Örebro University

Top Papers

  1. 1
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  3. 3
    Combining task and path planning for a humanoid two-arm robotic system
    26 citations · 2012

Key Collaborators

Contact & Links

Available for collaboration
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