Tiago Pereira

About

Tiago Pereira is a robotics researcher whose work spans autonomous navigation, multi-robot coordination, and motion planning for perception tasks. His research addresses fundamental challenges in enabling robots to operate intelligently and collaboratively in real-world environments, with particular emphasis on making robotic systems more capable and efficient. Among his most recognized contributions is his work on the Pepper humanoid robot, where he developed methods to enhance autonomous navigation and personalized human-robot interaction — his most cited work with 16 citations. Pereira has also made meaningful advances in multi-robot exploration and planning, introducing innovative tools such as robot-dependent reachability maps and topological map-based coordination frameworks that allow teams of robots to divide and conquer complex environments efficiently. A distinctive thread throughout his research is the development of visibility maps — geometric representations that capture a robot's sensing and motion reach — which he extended to arbitrarily shaped robots and applied to optimal perception planning problems. His PA* algorithm elegantly balances motion and sensing costs to find optimal paths for perception tasks. With contributions spanning heterogeneous multi-agent planning and remote robot instruction sharing, Pereira's body of work reflects a broad and practically grounded vision for intelligent, cooperative robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Setting Up Pepper For Autonomous Navigation And Personalized Interaction With Users

   16 citations · 2017
2. 2
   Coordination for Multi-robot Exploration Using Topological Maps

   9 citations · 2014
3. 3
   Multi-robot Planning Using Robot-Dependent Reachability Maps

   6 citations · 2015
4. 4
   Optimal Perception Planning with Informed Heuristics Constructed from Visibility Maps

   5 citations · 2018
5. 5
   Visibility maps for any-shape robots

   5 citations · 2016
6. 6
   Multi-Robot Planning for Perception of Multiple Regions of Interest

   5 citations · 2017
7. 7
   Improving Heuristics of Optimal Perception Planning Using Visibility Maps

   4 citations · 2016
8. 8
   Heterogeneous multi-agent planning using actuation maps

   3 citations · 2018
9. 9
   Help Me! Sharing of Instructions Between Remote and Heterogeneous Robots

   3 citations · 2016
10. 10
    PA*: Optimal Path Planning for Perception Tasks

    3 citations · 2016

Key Collaborators

Contact & Links