2 citations · 2 across the 5 of their papers we have counts for
6 papers
Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference
Daria de tinguy, Tim Verbelen, Emilio Gamba +1
Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on predefined maps or extensive tr…
Bio-Inspired Topological Autonomous Navigation with Active Inference in Robotics
Daria de Tinguy, Tim Verbelen, Emilio Gamba +1
Achieving fully autonomous exploration and navigation remains a critical challenge in robotics, requiring integrated solutions for localisation, mapping, decision-making and motion…
Navigation and Exploration with Active Inference: from Biology to Industry
Daria de Tinguy, Tim Verbelen, Bart Dhoedt
By building and updating internal cognitive maps, animals exhibit extraordinary navigation abilities in complex, dynamic environments. Inspired by these biological mechanisms, we p…
Learning Dynamic Cognitive Map with Autonomous Navigation
Daria de Tinguy, Tim Verbelen, Bart Dhoedt
Inspired by animal navigation strategies, we introduce a novel computational model to navigate and map a space rooted in biologically inspired principles. Animals exhibit extraordi…
Representing Positional Information in Generative World Models for Object Manipulation
Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen +2
Object manipulation capabilities are essential skills that set apart embodied agents engaging with the world, especially in the realm of robotics. The ability to predict outcomes o…
GenRL: Multimodal-foundation world models for generalization in embodied agents
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt +2
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement learning (RL) is hard to scale up as it requir…