Biomimicry has inspired the evolution of robotics toward greater autonomy, adaptability, and symbiosis with humans and dynamic environments. However, current robotic systems still face major challenges in recapitulating the high-efficiency decision-making capabilities of the human brain under complex and dynamic conditions. Here, we present Brainobot, a biohybrid robotic system that establishes a brain organoid controller as a high-level robotic decision-making layer for closed-loop embodiment. By leveraging brain organoid reservoir computing, Brainobot interacts with dynamic environments by receiving and processing sensory inputs and generating motor actions. As a proof-of-concept demonstration, Brainobot is implemented in a humanoid robotic system to perform real-world tasks, including object grasping and laser chasing. Interestingly, Brainobot exhibits unique features, including cross-task adaptivity, high computing efficiency, and low energy consumption. Thus, our approach may provide insights for advancing robotic embodiment and understanding biological decision-making.
Cai, H., Tian, C., Yang, Y., Xing, Y., Hong, Z., Chu, H., Wang, J., Ao, Z., Meyer, J. S., Friend, J., Tchieu, J., Gu, M., Hyun, I., Mackie, K., Liu, L., Guo, F.
Advertisement
Stats
- Recommendations n/a n/a positive of 0 vote(s)
- Views 18
- Comments 0