Per Rutquist
Papers
1
Total Citations
36
H-Index
1
About
Per Rutquist is a leading researcher in robotics and autonomous systems, with a primary focus on safe motion planning and model predictive control (MPC) in dynamic environments. His most influential work, "CIAO⁎: MPC-based Safe Motion Planning in Predictable Dynamic Environments" (2020), has garnered 36 citations and addresses a critical challenge in robotics: ensuring collision avoidance when robots operate alongside humans or other moving agents. By integrating MPC with a novel search-based planning framework, Rutquist’s approach enables real-time, provably safe navigation in shared spaces—a breakthrough for applications in manufacturing, logistics, and service robotics. His contributions bridge the gap between theoretical optimization and practical deployment, offering guarantees that were previously lacking in dynamic settings. Beyond this paper, Rutquist’s work has advanced the field of predictive control, influencing how researchers design algorithms that balance safety, efficiency, and adaptability. His research is essential reading for students and engineers working on autonomous navigation, human-robot interaction, and real-time decision-making under uncertainty.
Research Focus
Key Achievements
Top Papers
- 1CIAO⁎: MPC-based Safe Motion Planning in Predictable Dynamic Environments36 citations · 2020