Wireless motion control of a swimming eel-machine hybrid robot.

Abstract

This study presents a flexible aquatic swimming robot, which is a promising candidate for underwater search and detection missions. The robot is a living eel fitted with a wireless electronic backpack stimulator attached to its dorsal region. Leveraging the eel's inherent self-balancing and self-adaptation abilities, the robot can adapt seamlessly to complex underwater environments without the need for sophisticated controllers. Lateral line stimulation allows the robot to execute forward and backward swimming, as well as left and right curls. We graded the forward and backward swimming speed by varying the stimulus frequency and pulse width. The optimal stimulus parameters are as follows: amplitude 3.0-4.5 V, frequency 5-20 Hz, and pulse width 40-60 ms. The maximum success rates for forward and backward swimming responses to stimuli were approximately 96% and 77%, respectively. Utilizing lower pulse frequencies (5-20 Hz) and wider pulse widths (40-60 ms) facilitated sustained and efficient activation of the lateral line neural system. Electrical stimulation of the lateral line increases the eel's forward swimming speed by approximately 70%, while the electronic backpack draws only 48.1 mW of external power. Compared to bio-inspired robots, the eel-machine hybrid robot consumes 1.5 to 1100 times less external power per unit mass. The remarkable efficiency of this bio-robot enhances its performance in tasks such as underwater cave exploration.