Global Vision-Based Formation Control of Soft Robotic Fish Swarm

Abstract

Possessing the attributes of high adaptability and low cost, soft robotic individuals can further coordinate and form into a swarming system, enhancing the performances as well as functions in practical applications. However, the formation control of soft robotic swarm remains challenging mainly due to the limitation in relatively low precision and slow response of the soft actuators. In this work, a soft robotic fish swarm system with global vision positioning was studied. The soft robotic fish used in the project is driven by a hybrid powercontrol system, in which the soft dielectric elastomers and the rigid electrical servo provide forward propulsion and controllable steering function, respectively. Results show that soft robotic fish swarm can quickly shift their formations, mimicking three typical swarming behaviors of natural creatures: highly parallel group, encircling, and torus. The system design and controlling principles of the soft robotic fish swarm may guide the future research of soft robots and robotic swarms, specifically for underwater applications.

Decentralized Circle Formation Control for Fish-like Robots in the Real-world via Reinforcement Learning

“…Like other similar works [13], [14], [7] did, this paper considers the circle formation control in planar. As shown in Fig.…”

“…To the best of our knowledge, there are only two works that use physical fish-like robots for the circle formation control experiments [13], [14]. In [13], by combining active disturbance rejection control and proportional navigation law, the bottom-level motion controller of a single robot is proposed, which includes the target position control and target pose control.…”

“…Then, with the aid of the motion controller, each of the three fish-like robots swims towards its individual virtual target position and posture to formulate the circle formation in a plane. Similarly, in [14], through the position and posture control of the singe agent by the proportional controller, three soft fish-like robots swim on a common circle in a plane. However, both of them consider the circle formation control of fish-like robots through the bottom-level motion control of a single robot, thus they both emphasize the design of the robust dynamic model of their specific robots rather than the circle formation methods.…”

Planar Formation Control of a School of Robotic Fish: Theory and Experiments

“…Here, we present control laws that stabilize planar formations of a school of such robotic fish (Figure 1). Related work involving formation experiments of fish robots propelled by tail flapping was presented in (Berlinger et al, 2021;Zhang et al, 2021). In (Berlinger et al, 2021), a school of fish robots achieves circular formations and other collective behaviors using vision-based behaviors based on relative position.…”

“…In (Berlinger et al, 2021), a school of fish robots achieves circular formations and other collective behaviors using vision-based behaviors based on relative position. Similarily, in (Zhang et al, 2021), parallel and circular formations are achieved using an overhead camera to provide absolute positions of all the agents. Our work differs in that we investigate synchronized motion of multiple fish robots driven by an internal reaction wheel.…”