Facundo Pessacg

About

Facundo Pessacg is a robotics researcher whose work bridges the gap between autonomous navigation and educational technology. His primary research areas include multi-agent robotic exploration, visual-inertial odometry, and the application of robotics in educational settings. Pessacg’s most influential contribution is his behavior-based approach for educational robotics activities, which has garnered 58 citations and provides a structured methodology for introducing inexperienced students to robotics in classrooms and outreach programs. In the domain of autonomous navigation, he has developed sophisticated algorithms for visual-inertial “teach and repeat” systems, enabling aerial robots to autonomously retrace learned paths using only stereo and inertial data—a critical capability for resource-constrained unmanned aerial vehicles. His work on long-horizon active SLAM systems for multi-agent coordinated exploration (11 citations) addresses the challenge of efficiently mapping unknown environments while maintaining estimation accuracy across multiple autonomous agents. Through these contributions, Pessacg has advanced both the practical deployment of autonomous robots in real-world scenarios and the pedagogical frameworks that make robotics accessible to new learners.

Research Focus

Key Achievements

Top Papers

1. 1
   A Behavior-Based Approach for Educational Robotics Activities

   58 citations · 2012
2. 2
   Visual-inertial teach and repeat

   13 citations · 2020
3. 3
   Long-Horizon Active SLAM system for multi-agent coordinated exploration

   11 citations · 2019
4. 4
   Visual-Inertial Teach & Repeat for Aerial Robot Navigation

   4 citations · 2019

Key Collaborators

Contact & Links