Pedro Trindade

About

Pedro Trindade is a researcher at the forefront of assistive robotics, dedicated to developing intelligent systems that enhance the quality of life for the elderly and individuals with care needs. His work centers on human-robot interaction, human activity learning, and knowledge-based reasoning for robot manipulation. Trindade’s major contributions include a novel human activity learning system for assistive robots, which uses an RGB-depth sensor and a classifier ensemble to recognize and execute daily tasks—a system that has garnered 35 citations. He has also advanced robot grasp synthesis by enabling robots to reason from human demonstrations, bridging the gap between human dexterity and robotic manipulation. Notably, Trindade led the development of a service robot designed for natural social interaction with the elderly, integrating intelligent services for home care. His exploration of transfer learning in assistive robotics further pushes the boundaries, allowing robots to adapt knowledge from human domains to improve performance in real-world settings. With a clear focus on practical, human-centered solutions, Trindade’s work is shaping the future of ambient assisted living, making technology more intuitive and supportive for aging populations.

Research Focus

Key Achievements

Top Papers

1. 1
   Human activity learning for assistive robotics using a classifier ensemble

   35 citations · 2018
2. 2
   Knowledge-based reasoning from human grasp demonstrations for robot grasp synthesis

   22 citations · 2014
3. 3
   On the development of a service robot for social interaction with the elderly

   10 citations · 2015
4. 4
   Learning Human Activities for Assisted Living Robotics

   3 citations · 2017
5. 5
   Transfer Learning in Assistive Robotics: From Human to Robot Domain

   2 citations · 2019

Key Collaborators

Contact & Links