Autonomous Optimization of Swimming Gait in a Fish Robot With Multiple Onboard Sensors

Autonomous gait optimization is an essential survival ability for mobile robots. However, it remains a challenging task for underwater robots. This paper addresses this problem for the locomotion of a bio-inspired robotic fish and aims at identifying fast swimming gait autonomously by the robot. Our approach for learning locomotion controllers mainly uses three components: 1) a biological concept of central pattern generator to obtain specific gaits; 2) an onboard sensory processing center to discover the environment and to evaluate the swimming gait; and 3) an evolutionary algorithm referred to as particle swarm optimization. A key aspect of our approach is the swimming gait of the robot is optimized autonomously, equivalent to that the robot is able to navigate and evaluate its swimming gait in the environment by the onboard sensors, and simultaneously run a built-in evolutionary algorithm to optimize its locomotion all by itself. Forward speed optimization experiments conducted on the robotic fish demonstrate the effectiveness of the developed autonomous optimization system. The latest results show that our robotic fish attained a maximum swimming speed of 1.011 BL/s (40.42 cm/s) through autonomous gait optimization, faster than any of the robot's previously recorded speeds

Development of Modular Bio-Inspired Autonomous Underwater Vehicle for Close Subsea Asset Inspection

To reduce human risk and maintenance costs, Autonomous Underwater Vehicles (AUVs) are involved in subsea inspections and measurements for a wide range of marine industries such as offshore wind farms and other underwater infrastructure. Most of these inspections may require levels of manoeuvrability similar to what can be achieved by tethered vehicles, called Remotely Operated Vehicles (ROVs). To extend AUV intervention time and perform closer inspection in constrained spaces, AUVs need to be more efficient and flexible by being able to undulate around physical constraints. A biomimetic fish-like AUV known as RoboFish has been designed to mimic propulsion techniques observed in nature to provide high thrust efficiency and agility to navigate its way autonomously around complex underwater structures. Building upon advances in acoustic communications, computer vision, electronics and autonomy technologies, RoboFish aims to provide a solution to such critical inspections. This paper introduces the first RoboFish prototype that comprises cost-effective 3D printed modules joined together with innovative magnetic coupling joints and a modular software framework. Initial testing shows that the preliminary working prototype is functional in terms of water-tightness, propulsion, body control and communication using acoustics, with visual localisation and mapping capability

Towards Fault Diagnosis in Reconfigurable Robot

東京電機大学201

Online optimization of swimming and crawling in an amphibious snake robot

An important problem in the control of locomotion of robots with multiple degrees of freedom (e.g., biomimetic robots) is to adapt the locomotor patterns to the properties of the environment. This article addresses this problem for the locomotion of an amphibious snake robot, and aims at identifying fast swimming and crawling gaits for a variety of environments. Our approach uses a locomotion controller based on the biological concept of central pattern generators (CPGs) together with a gradient-free optimization method, Powell’s method. A key aspect of our approach is that the gaits are optimized online, i.e., while moving, rather than as an off-line optimization process. We present various experiments with the real robot and in simulation: swimming, crawling on horizontal ground, and crawling on slopes. For each of these different situations, the optimized gaits are compared with the results of systematic explorations of the parameter space. The main outcomes of the experiments are: 1) optimal gaits are significantly different from one medium to the other; 2) the optimums are usually peaked, i.e., speed rapidly becomes suboptimal when the parameters are moved away from the optimal values; 3) our approach finds optimal gaits in much fewer iterations than the systematic search; and 4) the CPG has no problem dealing with the abrupt parameter changes during the optimization process. The relevance for robotic locomotion control is discussed

Control and coordination of robotic fish

Het verbazingwekkende dynamische gedrag van scholen vissen en andere groepen sociale dieren in de natuur zijn in de afgelopen jaren in de belangstelling komen te staan van multidisciplinair onderzoek. In dit proefschrift passen we fundamentele gereedschappen uit de regeltechniek toe op biologische systemen om de regeling en coördinatie van robot multi-agent systemen bestuderen. We maken daarbij gebruik van robotvis teams die de natuur nabootsen. Als eerste onderzoeken we de motoriek van een individuele robotvis met als doel de uitstekende motorische vaardigheden van echte vissen na te bootsen. Vervolgens ontwerpen we gedistribueerde regelingen voor formaties van zwemmende robotvissen, die sinusoïde lichaamsgolven genereren in antifase. Deze regeling is geïnspireerd door de observatie dat formaties van gesynchroniseerde vissen mogelijkerwijs met een hogere energie efficiëntie zwemmen. Als derde presenteren we een evolutionair spel model om groepen robotvissen aan te sturen, dat gebaseerd is op het gecoördineerde gedrag van vissen in scholen en andere collectieve bewegingen van sociale dieren. Daarbij bestuderen we de opkomst en evolutie van samenwerking tussen de vissen in een multi-robotvis water polo wedstrijd. Gebruik makend van deze gereedschappen en evolutionaire speltheorie, ontwikkelen we tot slot een multi-robotvis setup om een nieuw kader te construeren voor de studie van diversificatie van persoonlijkheden en de opkomst van leiderschap, die cruciaal zijn voor de voltooiing van groepstaken