RESUMO
Soft robotics is closely related to embodied intelligence in the joint exploration of the means to achieve more natural and effective robotic behaviors via physical forms and intelligent interactions. Embodied intelligence emphasizes that intelligence is affected by the synergy of the brain, body, and environment, focusing on the interaction between agents and the environment. Under this framework, the design and control strategies of soft robotics depend on their physical forms and material properties, as well as algorithms and data processing, which enable them to interact with the environment in a natural and adaptable manner. At present, embodied intelligence has comprehensively integrated related research results on the evolution, learning, perception, decision making in the field of intelligent algorithms, as well as on the behaviors and controls in the field of robotics. From this perspective, the relevant branches of the embodied intelligence in the context of soft robotics were studied, covering the computation of embodied morphology; the evolution of embodied AI; and the perception, control, and decision making of soft robotics. Moreover, on this basis, important research progress was summarized, and related scientific problems were discussed. This study can provide a reference for the research of embodied intelligence in the context of soft robotics.
RESUMO
The soft organisms in nature have always been a source of inspiration for the design of soft arms and this paper draws inspiration from the octopus's tentacle, aiming at a soft robot for moving flexibly in three-dimensional space. In the paper, combined with the characteristics of an octopus's tentacle, a cable-driven soft arm is designed and fabricated, which can motion flexibly in three-dimensional space. Based on the TensorFlow framework, a data-driven model is established, and the data-driven model is trained using deep reinforcement learning strategy to realize posture control of a single soft arm. Finally, two trained soft arms are assembled into an octopus-inspired biped walking robot, which can go forward and turn around. Experimental analysis shows that the robot can achieve an average speed of 7.78 cm/s, and the maximum instantaneous speed can reach 12.8 cm/s.
RESUMO
In order to increase the compatibility between underwater robots and the underwater environment and inspired by the coconut octopus's underwater bipedal walking, a method was proposed for bipedal walking for an underwater soft robot based on a spring-loaded inverted pendulum (SLIP) model. Using the characteristics of octopus tentacles rolling on the ground, a wrist arm was designed using the cable-driven method, and an underwater SLIP bipedal walking model was established, which makes an underwater soft robot more suitable for moving on uneven ground. An underwater bipedal walking soft robot based on coconut octopus was then designed, and a machine vision algorithm was used to extract the motion information for analysis. Experimental analysis shows that the underwater bipedal walking robot can achieve an average speed of 6.48 cm s-1, and the maximum instantaneous speed can reach 8.14 cm s-1.
