Propulsive Velocity Optimization of 3-Joint Fish Robot Using Genetic-Hill Climbing Algorithm

Vo, Tuong Quan; Kim, Hyoung Seok; Lee, Byung Ryong

doi:10.1016/s1672-6529(08)60140-7

Cited by 24 publications

(6 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Joint level control is implemented via various means like layered control architecture consisting of three layers, namely, (1) cognitive layer, (2) behavior layer and (3) swim pattern layer [38], remote control [31,32,75,76,88,108], CPG control [2, 3, 17-19, 21, 40, 41, 46, 54-56, 79, 80, 92, 120], serial communication [125], ¥ H control method [73,160], computed torque method [30,145], radio-control [110], speed controller [118], fuzzy logic control method [53,122], Bio-inspired distributed control [1,30], sinusoidal motion control [33, 62, 68-71, 77, 112], pitch control mechanism [48], PID based controller to control the robot speed by varying the frequency of link oscillation [39,162], simplified wave control method [109], hierarchical control algorithm, approximate control algorithm [124] and open loop control of links [1, 4, 35, 39, 44, 49, 52, 57, 59, 61, 63, 66, 68, 69, 72, 77, 89-91, 94-98, 107-109, 123, 127, 148, 162]. NAF [61] consisted of a master controller which controlled different local controller which was used for controlling the actuators.…”

Section: Level Of Autonomymentioning

confidence: 99%

Fish-inspired robots: design, sensing, actuation, and autonomy—a review of research

2016

View full text Add to dashboard Cite

Underwater robot designs inspired by the behavior, physiology, and anatomy of fishes can provide enhanced maneuverability, stealth, and energy efficiency. Over the last two decades, robotics researchers have developed and reported a large variety of fish-inspired robot designs. The purpose of this review is to report different types of fish-inspired robot designs based upon their intended locomotion patterns. We present a detailed comparison of various design features like sensing, actuation, autonomy, waterproofing, and morphological structure of fish-inspired robots reported in the past decade. We believe that by studying the existing robots, future designers will be able to create new designs by adopting features from the successful robots. The review also summarizes the open research issues that need to be taken up for the further advancement of the field and also for the deployment of fish-inspired robots in practice.

show abstract

Section: Level Of Autonomymentioning

confidence: 99%

Fish-inspired robots: design, sensing, actuation, and autonomy—a review of research

2016

View full text Add to dashboard Cite

show abstract

“…A well-known hill-climbing genetic algorithm [10] was used to solve previous mentioned model in Eq. (1)- (7).…”

Section: Results and Analysismentioning

confidence: 99%

Aviation Emergency Rescue Dispatching Plan Based on Route Optimization Model Considering Random Wind

2016

Proceedings of 2016 the 6th International Workshop on Computer Science and Engineering

View full text Add to dashboard Cite

As an effective means of nature disaster relief, aviation emergency rescue is widely used in many countries. Aviation emergency rescue dispatching plan plays a dominant role that guarantees the efficient implementation of aviation emergency rescue. The conventional dispatching plan without considering random wind factor leads to non-precise quick-responsive scheme and safe issue. In this paper, an aviation emergency rescue framework considering the influence of random wind at flight trajectory is proposed. In this framework, the predicted wind information at disaster area is updated by unscented Kalman filtering (UKF) technology. Then, the motion model of rescue airplane is built by fusing the effect of random wind. An optimization model aiming at maximizing satisfaction index of rescue priority and minimizing total rescue flight distance is formulated. Finally, hill-climbing genetic algorithm is used to solve the mentioned multiple-targets model. A case study with a real earthquake disaster occurring in Sichuan Province is conducted. The results show that the obtained dispatching plan considering the constraints of updated wind speed and direction is more applicable for real operation.

show abstract

“…The same algorithm was reported to be used in finding the maximal propulsive velocity of a robotic fish. [ 43 ]…”

Section: Introductionmentioning

confidence: 99%

Modeling and Control of a Soft Robotic Fish with Integrated Soft Sensing

Lin

Siddall

Fukushima

et al. 2021

Advanced Intelligent Systems

View full text Add to dashboard Cite

Soft robotics can be used not only as a means of achieving novel, more lifelike forms of locomotion, but also as a tool to understand complex biomechanics through the use of robotic model animals. Herein, the control of the undulation mechanics of an entirely soft robotic subcarangiform fish is presented, using antagonistic fast‐PneuNet actuators and hyperelastic eutectic gallium–indium (eGaIn) embedded in silicone channels for strain sensing. To design a controller, a simple, data‐driven lumped parameter approach is developed, which allows accurate but lightweight simulation, tuned using experimental data and a genetic algorithm. The model accurately predicts the robot's behavior over a range of driving frequencies and a range of pressure amplitudes, including the effect of antagonistic co‐contraction of the soft actuators. An amplitude controller is prototyped using the model and deployed to the robot to reach the setpoint of a tail‐beat amplitude using fully soft and real‐time strain sensing.

show abstract

Propulsive Velocity Optimization of 3-Joint Fish Robot Using Genetic-Hill Climbing Algorithm

Cited by 24 publications

References 9 publications

Fish-inspired robots: design, sensing, actuation, and autonomy—a review of research

Fish-inspired robots: design, sensing, actuation, and autonomy—a review of research

Aviation Emergency Rescue Dispatching Plan Based on Route Optimization Model Considering Random Wind

Modeling and Control of a Soft Robotic Fish with Integrated Soft Sensing

Contact Info

Product

Resources

About