Multimodal VAE Active Inference Controller

by   Cristian Meo, et al.

Active inference, a theoretical construct inspired by brain processing, is a promising alternative to control artificial agents. However, current methods do not yet scale to high-dimensional inputs in continuous control. Here we present a novel active inference torque controller for industrial arms that maintains the adaptive characteristics of previous proprioceptive approaches but also enables large-scale multimodal integration (e.g., raw images). We extended our previous mathematical formulation by including multimodal state representation learning using a linearly coupled multimodal variational autoencoder. We evaluated our model on a simulated 7DOF Franka Emika Panda robot arm and compared its behavior with a previous active inference baseline and the Panda built-in optimized controller. Results showed improved tracking and control in goal-directed reaching due to the increased representation power, high robustness to noise and adaptability in changes on the environmental conditions and robot parameters without the need to relearn the generative models nor parameters retuning.


page 1

page 5


Adaptation through prediction: multisensory active inference torque control

Adaptation to external and internal changes is major for robotic systems...

A Novel Adaptive Controller for Robot Manipulators based on Active Inference

More adaptive controllers for robot manipulators are needed, which can d...

End-to-End Pixel-Based Deep Active Inference for Body Perception and Action

We present a pixel-based deep Active Inference algorithm (PixelAI) inspi...

Multimodal representation models for prediction and control from partial information

Similar to humans, robots benefit from interacting with their environmen...

Making Sense of Vision and Touch: Learning Multimodal Representations for Contact-Rich Tasks

Contact-rich manipulation tasks in unstructured environments often requi...

Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem

Despite the potential of active inference for visual-based control, lear...

Active Inference for Integrated State-Estimation, Control, and Learning

This work presents an approach for control, state-estimation and learnin...