About

Diego Pardo is a leading roboticist whose work spans legged locomotion, compliant manipulation, and surgical robotics. His most influential contribution is in force estimation for robot manipulators, where he developed a sensorless method combining task-oriented dynamics model learning with a robust disturbance observer—a technique that has garnered over 100 citations and enables safer, more adaptive physical interaction. In legged robotics, Pardo has made foundational advances in motion planning and control. His vertex-based ZMP constraint formulation for fast trajectory optimization (83 citations) and his online walking motion algorithm that simultaneously optimizes center-of-mass trajectory and footholds (46 citations) have become key references for quadruped locomotion. He also contributed to the emerging field of robot-assisted laser microsurgery, developing feed-forward incision control for soft tissue and advancing micro-technologies for endoscopic procedures. Beyond engineering, Pardo has explored human-robot interaction, studying how children build long-term social bonds with robots for therapeutic applications. His work on social robot paradigms and child-robot relationships demonstrates a rare breadth—from low-level control theory to high-level social dynamics—making him a versatile and impactful researcher in modern robotics.

Research Focus

Key Achievements

11
H-Index
22
Papers
497
Total Citations
23
Avg Citations/Paper
🏆 Most Cited Paper
External force estimation during compliant robot manipulation
100 citations · 2013
📈 Most Prolific Year: 2017 (4 Papers)
🤝 Key Collaborators: 53
🏛 Institutions: Italian Institute of Technology, ETH Zurich, Cidete (Spain), Universitat Politècnica de Catalunya, ZHAW Zurich University of Applied Sciences

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago