1. Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
- Author
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Alhakami, Mohannad, Ashley, Dylan R., Dunham, Joel, Faccio, Francesco, Feron, Eric, and Schmidhuber, Jürgen
- Subjects
Computer Science - Robotics ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,I.2.9 ,I.2.6 - Abstract
Artificial intelligence has made great strides in many areas lately, yet it has had comparatively little success in general-use robotics. We believe one of the reasons for this is the disconnect between traditional robotic design and the properties needed for open-ended, creativity-based AI systems. To that end, we, taking selective inspiration from nature, build a robust, partially soft robotic limb with a large action space, rich sensory data stream from multiple cameras, and the ability to connect with others to enhance the action space and data stream. As a proof of concept, we train two contemporary machine learning algorithms to perform a simple target-finding task. Altogether, we believe that this design serves as a first step to building a robot tailor-made for achieving artificial general intelligence., Comment: 5 pages in main text + 1 page of references, 7 figures in main text; source code available at https://github.com/dylanashley/robot-limb-testai
- Published
- 2024