Maja Karasalo

KTH Royal Institute of Technology

Papers

6

Total Citations

39

H-Index

4

About

Maja Karasalo’s research lies at the intersection of multi-robot coordination, formation control, and contour reconstruction, with a focus on enabling autonomous systems to operate effectively under limited sensor information. Her most significant contributions include pioneering a recursive smoothing spline approach for contour reconstruction, allowing robots to approximate and match obstacle boundaries in real time—work that has garnered 11 citations in its seminal 2007 paper. She also advanced multi-robot formation control and terrain servoing, demonstrating globally stable control for line formations with noisy sensor data, validated through experiments with Khepera robots. Her 2005 paper on multi-robot formation control with limited sensors has accumulated 8 citations, while subsequent experimental validations of her spline algorithms have added another 12 citations. Karasalo’s work is notable for its practical experimental validation, bridging theoretical stability proofs with real-world robotic implementations. Her research on robust formation adaptation and heterogeneous sensor teams has laid groundwork for resilient multi-agent systems, making her a key contributor to the fields of distributed robotics and autonomous navigation.

Research Focus

Key Achievements

4
H-Index
6
Papers
39
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Contour Reconstruction and Matching Using Recursive Smoothing Splines
11 citations · 2007
📈 Most Prolific Year: 2007 (2 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: KTH Royal Institute of Technology

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago