Sensing the flow beneath the fins

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots

Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.

Recent progress on underwater soft robots: adhesion, grabbing, actuating, and sensing

The research on biomimetic robots, especially soft robots with flexible materials as the main structure, is constantly being explored. It integrates multi-disciplinary content, such as bionics, material science, mechatronics engineering, and control theory, and belongs to the cross-disciplinary field related to mechanical bionics and biological manufacturing. With the continuous development of various related disciplines, this area has become a hot research field. Particularly with the development of practical technologies such as 3D printing technology, shape memory alloy, piezoelectric materials, and hydrogels at the present stage, the functions and forms of soft robots are constantly being further developed, and a variety of new soft robots keep emerging. Soft robots, combined with their own materials or structural characteristics of large deformation, have almost unlimited degrees of freedom (DoF) compared with rigid robots, which also provide a more reliable structural basis for soft robots to adapt to the natural environment. Therefore, soft robots will have extremely strong adaptability in some special conditions. As a type of robot made of flexible materials, the changeable pose structure of soft robots is especially suitable for the large application environment of the ocean. Soft robots working underwater can better mimic the movement characteristics of marine life in the hope of achieving more complex underwater tasks. The main focus of this paper is to classify different types of underwater organisms according to their common motion modes, focusing on the achievements of some bionic mechanisms in different functional fields that have imitated various motion modes underwater in recent years (e.g., the underwater sucking glove, the underwater Gripper, and the self-powered soft robot). The development of various task types (e.g., grasping, adhesive, driving or swimming, and sensing functions) and mechanism realization forms of the underwater soft robot are described based on this article.

MEMS-Based Micro Sensors for Measuring the Tiny Forces Acting on Insects

Small insects perform agile locomotion, such as running, jumping, and flying. Recently, many robots, inspired by such insect performance, have been developed and are expected to be smaller and more maneuverable than conventional robots. For the development of insect-inspired robots, understanding the mechanical dynamics of the target insect is important. However, evaluating the dynamics via conventional commercialized force sensors is difficult because the exerted force and insect itself are tiny in strength and size. Here, we review force sensor devices, especially fabricated for measuring the tiny forces acting on insects during locomotion. As the force sensor, micro-force plates for measuring the ground reaction force and micro-force probes for measuring the flying force have mainly been developed. In addition, many such sensors have been fabricated via a microelectromechanical system (MEMS) process, due to the process precision and high sensitivity. In this review, we focus on the sensing principle, design guide, fabrication process, and measurement method of each sensor, as well as the technical challenges in each method. Finally, the common process flow of the development of specialized MEMS sensors is briefly discussed.

Estimation System of Disturbance Force and Torque for Underwater Robot Based on Artificial Lateral Line

The motion-control precision of a shallow-sea underwater robot is seriously affected by external disturbances such as wind, waves and ocean currents. Due to the lack of a specialized disturbance-sensor system, the disturbance force and torque cannot be sensed effectively. Inspired by bionics, an artificial lateral-line system for estimating external disturbances of an underwater robot is presented in this paper. In the system, the pressure of water is first collected through the pressure-sensor array. Then, the pressure data is processed by a series of algorithms, and the disturbance force and torque are observed from the data. Both multiple linear regression and the artificial neural network method are used to fit the mathematical models of the disturbances. Finally, the system is validated experimentally to be effective and practical. The underwater robot senses the disturbance force and torque from the water indirectly through the artificial lateral-line system, which will improve the accuracy of motion control.

Materials, Actuators, and Sensors for Soft Bioinspired Robots

Biological systems can perform complex tasks with high compliance levels. This makes them a great source of inspiration for soft robotics. Indeed, the union of these fields has brought about bioinspired soft robotics, with hundreds of publications on novel research each year. This review aims to survey fundamental advances in bioinspired soft actuators and sensors with a focus on the progress between 2017 and 2020, providing a primer for the materials used in their design.

Dual-sensor fusion based attitude holding of a fin-actuated robotic fish

In nature, the lateral line system (LLS) is a critical sensor organ of fish for rheotaxis in complex environments. Inspired by the LLS, numbers of artificial lateral line systems (ALLSs) have been designed to the fish-like robots for flow field perception, assisting the robots to be stable in the face of flow disturbances. However, almost all pressure sensor based ALLSs face the challenge of the low signal to noise ratio (SNR), resulting in inaccurate perception information. To solve this problem, this paper describes a dual-sensor fusion method by integrating the ALLSs with the inertial measurement unit (IMU), and shows the excellent performance by a higher precision and lower latency attitude holding of robotic fish. First, low-pass filtering is performed on ALLS data with low-SNR. Second, the ALLS data is mapped to the angle of attack based on an artificial neural network. Finally, a fusion perception method is established based on the time correlation between ALLS and IMU. To demonstrate the efficacy of our proposed method, we compare the result of attitude holding by three methods (dual-sensor fusion method, IMU based method, and ALLS based method). Furthermore, dual-sensor fusion method is tested at varied flow velocities and varied desired angles of attack, indicating that the algorithm can enable the robotic fish to perform dynamic movements in the incoming flow. This work provides a method for the attitude control of autonomous underwater vehicles (AUVs) by fusing the sensory data of ALLS and IMU, which is also applicable to other flow sensors and IMU.

Constriction canal assisted artificial lateral line system for enhanced hydrodynamic pressure sensing

With the assistance of mechanosensory lateral line system, fish can perceive minute water motions in complex underwater environments. Inspired by the constriction within canal nearby canal neuromast in fish lateral line system, we proposed a novel canal artificial lateral line (CALL) device with constriction in canal nearby the sensing element. The designed CALL device consisted of a poly(vinylidene fluoride-trifluoroethylene)/polyimide cantilever as the sensing element and a polydimethylsiloxane (PDMS) microfluid canal. Two types of CALL devices, i.e., CALL with straight canal (S-CALL) and CALL with constriction canal (C-CALL), were developed and characterized employing a dipole source. Experimental results showed that the proposed C-CALL device achieved a pressure gradient detection limit of 0.64 Pa m^-1, which was much lower than the S-CALL device. It indicates that the constriction in the canal nearby the sensing element could enhance the hydrodynamic pressure sensing performance of the CALL device. In addition, the constriction could modify the frequency response of the CALL device, and the C-CALL device achieved higher voltage output than S-CALL in high-frequency domain.

Flow field perception based on the fish lateral line system

Fish are able to perceive the surrounding weak flow and pressure variations with their mechanosensory lateral line system, which consists of a superficial lateral line for flow velocity detection and a canal lateral line for flow pressure gradient perception. Achieving a better understanding of the flow field perception algorithms of the lateral line can contribute not only to the design of highly sensitive flow sensors, but also to the development of underwater smart skin with good hydrodynamic imaging properties. In this review, we discuss highly sensitive flow-sensing mechanisms for superficial and canal neuromasts and flow field perception algorithms. Artificial lateral line systems with different transduction mechanisms are then described with special emphasis on the recent innovations in the field of polymer-based artificial flow sensors. Finally, we discuss our perspective of the technological challenges faced while improving flow sensitivity, durability, and sensing fusion schemes.

Filtered Mechanosensing Using Snapping Composites with Embedded Mechano-Electrical Transduction

Mechanosensing is ubiquitous in natural systems. From the skin ridges of our finger tips to the microscopic ion channels in cells, mechanosensors allow organisms to probe their environment and gather information needed for processing, decision making, and actuation. Despite technological advances in synthetic mechanosensing, it remains challenging to achieve this functionality at the scale of large stiff structures where both the amount of data to sense locally and the diversity of input stresses that the sensors have to withstand require highly tunable systems. Filtered sensing using mechanical displacement is an effective strategy developed by organisms to cope with large sets of stimuli. Inspired by this biological strategy, we fabricate bistable elements that can passively filter mechanical inputs, translate them into electrical signals, and be reset to their original sensing state using an external magnetic field. These multiple functionalities are achieved using hierarchically structured composites that can be arranged in large-area arrays. The filtering capability and fast passive response of our mechanosensors are experimentally demonstrated using simple electrical circuits and magnets. Thanks to their scalability and applicability to a wide range of material systems, these low-power sensors are avenues for the fabrication of load-bearing structures that are able to sense, compute, communicate, and autonomously adapt in response to external magneto-mechanical stimuli.

Biomechanics in Soft Mechanical Sensing: From Natural Case Studies to the Artificial World

Living beings use mechanical interaction with the environment to gather essential cues for implementing necessary movements and actions. This process is mediated by biomechanics, primarily of the sensory structures, meaning that, at first, mechanical stimuli are morphologically computed. In the present paper, we select and review cases of specialized sensory organs for mechanical sensing-from both the animal and plant kingdoms-that distribute their intelligence in both structure and materials. A focus is set on biomechanical aspects, such as morphology and material characteristics of the selected sensory organs, and on how their sensing function is affected by them in natural environments. In this route, examples of artificial sensors that implement these principles are provided, and/or ways in which they can be translated artificially are suggested. Following a biomimetic approach, our aim is to make a step towards creating a toolbox with general tailoring principles, based on mechanical aspects tuned repeatedly in nature, such as orientation, shape, distribution, materials, and micromechanics. These should be used for a future methodical design of novel soft sensing systems for soft robotics.