Rodrigo Palma-Amestoy

About

Rodrigo Palma-Amestoy is a robotics researcher whose work centers on humanoid robot locomotion, robot vision, and damage mitigation, with a particular focus on applications in robotic soccer. His most significant contribution is the pioneering concept of "learning to fall," where he designed low-damage fall sequences for humanoid soccer robots—a critical innovation that addresses the inherent fragility of bipedal robots. This work, published in 2009, has garnered 47 citations and stands as his most influential paper. Palma-Amestoy also advanced robot vision systems through context-dependent color segmentation for Aibo robots and Bayesian spatiotemporal context integration, both of which improve perception under variable lighting conditions. As a member of the UChile Kiltros team, he contributed to the transfer of developments across RoboCup leagues, including the Standard Platform and Humanoid leagues. His research in real-time hybrid architectures for biped humanoids with active vision further underscores his commitment to robust, practical robotics. With a career spanning foundational work in fall safety and vision, Palma-Amestoy’s impact is felt in both the RoboCup community and broader humanoid robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Learning to fall: Designing low damage fall sequences for humanoid soccer robots

   47 citations · 2009
2. 2
   Context - dependent color segmentation for Aibo robots

   9 citations · 2006
3. 3
   Bayesian Spatiotemporal Context Integration Sources in Robot Vision Systems

   6 citations · 2009
4. 4
   Designing Fall Sequences That Minimize Robot Damage in Robot Soccer

   4 citations · 2009
5. 5
   UChile Kiltros 2008 Team Description Paper

   4 citations · 2008
6. 6
   A Real-Time Hybrid Architecture for Biped Humanoids with Active Vision Mechanisms

   3 citations · 2010
7. 7
   UChile1 Strikes Back, 2006 Team Description Paper

   2 citations · 2006

Key Collaborators

Contact & Links