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FOCUS: Object-Centric World Models for Robotics Manipulation
Understanding the world in terms of objects and the possible interplays with them is an important cognition ability, especially in robotics manipulation, where many tasks require robot-object interactions.
Object-Centric Scene Representations using Active Inference
Representing a scene and its constituent objects from raw sensory data is a core ability for enabling robots to interact with their environment.
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models
Recently, deep learning methods have been proposed to learn a hidden state space structure purely from data, alleviating the experimenter from this tedious design task, but resulting in an entangled, non-interpreteable state space.
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