Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms
<|reference_start|>Towards a Robust Soft Baby Robot With Rich Interaction Ability for Advanced Machine Learning Algorithms: 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.<|reference_end|>
@article{alhakami2024towards,
    title={Towards a Robust Soft Baby Robot With Rich Interaction Ability for
  Advanced Machine Learning Algorithms},
    author={Mohannad Alhakami, Dylan R. Ashley, Joel Dunham, Francesco Faccio,
  Eric Feron, J"urgen Schmidhuber},
    journal={arXiv preprint arXiv:2404.08093},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.08093},
    primaryClass={cs.RO cs.AI cs.LG}
}