About

Dizan Vasquez is a leading researcher in mobile robotics, specializing in human-aware navigation and social robot motion. His work focuses on enabling robots to operate safely and naturally in human-populated environments, particularly urban pedestrian spaces. Vasquez is best known for pioneering the application of Inverse Reinforcement Learning (IRL) to robot navigation, as demonstrated in his highly cited 2014 paper (167 citations), which systematically compared IRL algorithms for modeling social interactions and reproducing pedestrian behavior. He made foundational contributions to human motion prediction, developing novel planning-based algorithms that anticipate people's movements by assuming they optimize cost functions (2016, 31 citations). Vasquez also led the autonomous navigation system for the European URUS project, achieving over 3.5 km of fully autonomous operation in real urban environments with Segway-based service robots (2011, 51 citations). His research on human-aware navigation for assistive robotics (2013, 35 citations) and intentional motion learning (2006) has shaped how robots understand and predict human intent. With a career spanning over a decade, Vasquez's work bridges machine learning, planning, and social robotics, making him a key figure in developing robots that can coexist with people in crowded, dynamic spaces.

Research Focus

Key Achievements

6
H-Index
6
Papers
313
Total Citations
52
Avg Citations/Paper
🏆 Most Cited Paper
Inverse Reinforcement Learning algorithms and features for robot navigation in crowds: An experimental comparison
167 citations · 2014
📈 Most Prolific Year: 2014 (1 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Institut national de recherche en sciences et technologies du numérique, École Polytechnique Fédérale de Lausanne, Université Pierre Mendès France, Université Grenoble Alpes

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