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Micromachines
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New Advances in Biomimetic Robots
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New Advances in Biomimetic Robots

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "A：Physics".

Deadline for manuscript submissions: closed (10 July 2022) | Viewed by 32265

Special Issue Editors

Prof. Dr. Zhangguo Yu

E-Mail Website
Guest Editor
Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: design, motion planning and control of humanoid robots
Prof. Dr. Marco Ceccarelli

E-Mail Website1 Website2 Website3
Guest Editor
LARM2: Laboratory of Robot Mechatronics, Department of Industrial Engineering, University of Rome Tor Vergata, Via del Politecnico 1, 00133 Roma, Italy
Interests: mechanism design mechanics of robots; robot design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomimetic robots, ranging in size from the micro-scale to humanoid-scale, feature some biological characteristics and functions, such as insect-like flying robots, quadruped robots and humanoid robots. Significant headway was made in biomimetic robots over the past few years. For example, the functionality of quadruped and humanoid robots progressed, with the developments of agile maneuverability, robust adaptability to terrain, dexterous manipulation and intelligent human–machine interaction, etc., such as fast walking, running, leaps, bounds, backflips, and navigation on uneven terrain. This Special Issue aims to provide an opportunity for researchers to present their recent developments in the technology of biomimetic robots. Topics of interest include, but are not limited to: system design, bionic sensing/actuation mechanisms, motion planning, balance control, manipulation, robot learning, human–humanoid interaction, and exoskeletons.

Prof. Dr. Zhangguo Yu
Prof. Dr. Marco Ceccarelli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomimetic robots
  • humanoid robots
  • quadruped robots
  • microrobots
  • kinematics and dynamics
  • system design
  • bionic actuation
  • bionic sensing
  • legged locomotion
  • balance control
  • motion planning and control
  • human-robot interaction
  • exoskeleton
  • prosthetics

Published Papers (15 papers)

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Research

18 pages, 16233 KiB  
Article
Symmetrical Efficient Gait Planning Based on Constrained Direct Collocation
by Boyang Chen, Xizhe Zang, Yue Zhang, Liang Gao, Yanhe Zhu and Jie Zhao
Micromachines 2023, 14(2), 417; https://0-doi-org.brum.beds.ac.uk/10.3390/mi14020417 - 10 Feb 2023
Viewed by 1258
Abstract
Biped locomotion provides more mobility and effectiveness compared with other methods. Animals have evolved efficient walking patterns that are pursued by biped robot researchers. Current researchers have observed that symmetry is a critical criterion to achieve efficient natural walking and usually realize symmetrical [...] Read more.
Biped locomotion provides more mobility and effectiveness compared with other methods. Animals have evolved efficient walking patterns that are pursued by biped robot researchers. Current researchers have observed that symmetry is a critical criterion to achieve efficient natural walking and usually realize symmetrical gait patterns through morphological characteristics using simplified dynamic models or artificial priors of the center of mass (CoM). However, few considerations of symmetry and energy consumption are introduced at the joint level, resulting in inefficient leg motion. In this paper, we propose a full-order biped gait planner in which the symmetry requirement, energy efficiency, and trajectory smoothness can all be involved at the joint level, and CoM motion is automatically determined without any morphological prior. In order to achieve a symmetrical and efficient walking pattern, we first investigated the characteristic of a completely symmetrical gait, and a group of nearly linear slacked constraints was designed for three phases of planning. Then a Constrained Direct Collocation (DIRCON)-based full-order biped gait planner with a weighted cost function for energy consumption and trajectory smoothness is proposed. A dynamic simulation with our newly designed robot model was performed in CoppliaSim to test the planner. Physical comparison experiments on a real robot device finally validated the symmetry characteristic and energy efficiency of the generated gait. In addition, a detailed presentation of the real biped robot is also provided. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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14 pages, 1949 KiB  
Article
Hybrid Bipedal Locomotion Based on Reinforcement Learning and Heuristics
by Zhicheng Wang, Wandi Wei, Anhuan Xie, Yifeng Zhang, Jun Wu and Qiuguo Zhu
Micromachines 2022, 13(10), 1688; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13101688 - 07 Oct 2022
Cited by 6 | Viewed by 2346
Abstract
Locomotion control has long been vital to legged robots. Agile locomotion can be implemented through either model-based controller or reinforcement learning. It is proven that robust controllers can be obtained through model-based methods and learning-based policies have advantages in generalization. This paper proposed [...] Read more.
Locomotion control has long been vital to legged robots. Agile locomotion can be implemented through either model-based controller or reinforcement learning. It is proven that robust controllers can be obtained through model-based methods and learning-based policies have advantages in generalization. This paper proposed a hybrid framework of locomotion controller that combines deep reinforcement learning and simple heuristic policy and assigns them to different activation phases, which provides guidance for adaptive training without producing conflicts between heuristic knowledge and learned policies. The training in simulation follows a step-by-step stochastic curriculum to guarantee success. Domain randomization during training and assistive extra feedback loops on real robot are also adopted to smooth the transition to the real world. Comparison experiments are carried out on both simulated and real Wukong-IV humanoid robots, and the proposed hybrid approach matches the canonical end-to-end approaches with higher rate of success, faster converging speed, and 60% less tracking error in velocity tracking tasks. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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Graphical abstract

19 pages, 6068 KiB  
Article
Design and Performance Analysis of LARMbot Torso V1
by Wenshuo Gao and Marco Ceccarelli
Micromachines 2022, 13(9), 1548; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091548 - 18 Sep 2022
Cited by 4 | Viewed by 1470
Abstract
In this paper, laboratory experiments of LARMbot torso V1 are reported in the third mode, thereby providing a testing characterization. Sensors were used to measure parameters including the contact force between the shoulder and cables, linear acceleration, angles of the torso body, and [...] Read more.
In this paper, laboratory experiments of LARMbot torso V1 are reported in the third mode, thereby providing a testing characterization. Sensors were used to measure parameters including the contact force between the shoulder and cables, linear acceleration, angles of the torso body, and power consumption. The results showed that the LARMbot torso V1 can bend successfully to the desired angles, and that it is able to complete a full motion smoothly. The LARMbot torso V1 can mimic human-like motiaons. Based on our analysis of the test results, improvements are suggested, and new designs are considered. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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18 pages, 7307 KiB  
Article
Dynamic Balancing of Humanoid Robot with Proprioceptive Actuation: Systematic Design of Algorithm, Software, and Hardware
by Yan Xie, Jiajun Wang, Hao Dong, Xiaoyu Ren, Liqun Huang and Mingguo Zhao
Micromachines 2022, 13(9), 1458; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091458 - 02 Sep 2022
Cited by 3 | Viewed by 1796
Abstract
For humanoid robots, maintaining a dynamic balance against uncertain disturbance is crucial, and this function can be achieved by coordinating the whole body to perform multiple tasks simultaneously. Researchers generally accept hierarchical whole-body control (WBC) to address this function. Although experts can build [...] Read more.
For humanoid robots, maintaining a dynamic balance against uncertain disturbance is crucial, and this function can be achieved by coordinating the whole body to perform multiple tasks simultaneously. Researchers generally accept hierarchical whole-body control (WBC) to address this function. Although experts can build feasible hierarchies using prior knowledge, real-time WBC is still challenging because it often requires a quadratic program with multiple inequality constraints. In addition, the torque tracking performance of the WBC algorithm will be affected by uncertain factors such as joint friction for a large transmission ratio proprioceptive-actuated robot. Therefore, the balance control of physical robots requires a systematic solution. In this study, a robot control system with high computing power and real-time communication ability, UBTMaster, is implemented to achieve a reduced WBC in real time. Based on these, a whole-body control scheme based on task priority for the dynamic balance of humanoid robots is implemented. After realizing the joint friction model identification, finally, a variety of balancing scenarios are tested on the Walker3 humanoid robot driven by the proprioceptive actuators to verify the effectiveness of the proposed scheme. The Walker3 robot exhibits excellent balance when multiple external disturbances occur simultaneously. For example, the two feet of the robot are subjected to tilt and displacement perturbations, respectively, while the torso is subjected to external shocks simultaneously. The experimental results show that the dynamic balance of the robot under multiple external disturbances can be achieved by using strictly hierarchical real-time WBC with a systematic design. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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26 pages, 10453 KiB  
Article
A Stability Training Method of Legged Robots Based on Training Platforms and Reinforcement Learning with Its Simulation and Experiment
by Weiguo Wu, Liyang Gao and Xiao Zhang
Micromachines 2022, 13(9), 1436; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091436 - 31 Aug 2022
Cited by 1 | Viewed by 1462
Abstract
This paper continues the proposed idea of stability training for legged robots with any number of legs and any size on a motion platform and introduces the concept of a learning-based controller, the global self-stabilizer, to obtain a self-stabilization capability in robots. The [...] Read more.
This paper continues the proposed idea of stability training for legged robots with any number of legs and any size on a motion platform and introduces the concept of a learning-based controller, the global self-stabilizer, to obtain a self-stabilization capability in robots. The overall structure of the global self-stabilizer is divided into three modules: action selection, adjustment calculation and joint motion mapping, with corresponding learning algorithms proposed for each module. Taking the human-sized biped robot, GoRoBoT-II, as an example, simulations and experiments in three kinds of motions were performed to validate the feasibility of the proposed idea. A well-designed training platform was used to perform composite random amplitude-limited disturbances, such as the sagittal and lateral tilt perturbations (±25°) and impact perturbations (0.47 times the robot gravity). The results show that the proposed global self-stabilizer converges after training and can dynamically combine actions according to the system state. Compared with the controllers used to generate the training data, the trained global self-stabilizer increases the success rate of stability verification simulations and experiments by more than 20% and 15%, respectively. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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20 pages, 7113 KiB  
Article
Design, Analysis and Experiments of Hexapod Robot with Six-Link Legs for High Dynamic Locomotion
by Jiawang Ma, Guanlin Qiu, Weichen Guo, Peitong Li and Gan Ma
Micromachines 2022, 13(9), 1404; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13091404 - 26 Aug 2022
Cited by 3 | Viewed by 2992
Abstract
An important feature of a legged robot is its dynamic motion performance. Traditional methods often improve the dynamic motion performance by reducing the moment of inertia of robot legs or by adopting quasi-direct drive actuators. This paper proposes a method to enhance the [...] Read more.
An important feature of a legged robot is its dynamic motion performance. Traditional methods often improve the dynamic motion performance by reducing the moment of inertia of robot legs or by adopting quasi-direct drive actuators. This paper proposes a method to enhance the dynamic performance of a legged robot by transmission mechanism. Specifically, we present a unique six-link leg mechanism that can implement a large output motion using a small drive motion. This unique feature can enhance the robots’ dynamic motion capability. Experiments with a hexapod robot verified the effectiveness of the mechanism. The experimental results showed that, when the steering gear of the robot rotates 1°, the toe can lift 7 mm (5% of body height), and the maximum running speed of the robot can reach 390 mm/s (130% of the moveable body length per second). Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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20 pages, 3783 KiB  
Article
Stable and Fast Planar Jumping Control Design for a Compliant One-Legged Robot
by Guifu Luo, Ruilong Du, Sumian Song, Haihui Yuan, Zhiyong Huang, Hua Zhou and Jason Gu
Micromachines 2022, 13(8), 1261; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13081261 - 05 Aug 2022
Cited by 2 | Viewed by 1572
Abstract
Compliant bipedal robots demonstrate a potential for impact resistance and high energy efficiency through the introduction of compliant elements. However, it also adds to the difficulty of stable control of the robot. To motivate the control strategies of compliant bipedal robots, this work [...] Read more.
Compliant bipedal robots demonstrate a potential for impact resistance and high energy efficiency through the introduction of compliant elements. However, it also adds to the difficulty of stable control of the robot. To motivate the control strategies of compliant bipedal robots, this work presents an improved control strategy for the stable and fast planar jumping of a compliant one-legged robot designed by the authors, which utilizes the concept of the virtual pendulum. The robot was modeled as an extended spring-loaded inverted pendulum (SLIP) model with non-negligible torso inertia, leg inertia, and leg damping. To enable the robot to jump forward stably, a foot placement method was adopted, where due to the asymmetric feature of the extended SLIP model, a variable time coefficient and an integral term with respect to the forward speed tracking error were introduced to the method to accurately track a given forward speed. An energy-based leg rest length regulation method was used to compensate for the energy dissipation due to leg damping, where an integral term, regarding jumping height tracking error, was introduced to accurately track a given jumping height. Numerical simulations were conducted to validate the effectiveness of the proposed control strategy. Results show that stable and fast jumping of compliant one-legged robots could be achieved, and the desired forward speed and jumping height could also be accurately tracked. In addition to that, using the proposed control strategy, the robust jumping performance of the robot could be observed in the presence of disturbances from state variables or uneven terrain. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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21 pages, 6109 KiB  
Article
Upright and Crawling Locomotion and Its Transition for a Wheel-Legged Robot
by Xuejian Qiu, Zhangguo Yu, Libo Meng, Xuechao Chen, Lingxuan Zhao, Gao Huang and Fei Meng
Micromachines 2022, 13(8), 1252; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13081252 - 04 Aug 2022
Cited by 6 | Viewed by 2720
Abstract
To face the challenge of adapting to complex terrains and environments, we develop a novel wheel-legged robot that can switch motion modes to adapt to different environments. The robot can perform efficient and stable upright balanced locomotion on flat roads and flexible crawling [...] Read more.
To face the challenge of adapting to complex terrains and environments, we develop a novel wheel-legged robot that can switch motion modes to adapt to different environments. The robot can perform efficient and stable upright balanced locomotion on flat roads and flexible crawling in low and narrow passages. For passing through low and narrow passages, we propose a crawling motion control strategy and methods for transitioning between locomotion modes of wheel-legged robots. In practical applications, the smooth transition between the two motion modes is challenging. By optimizing the gravity work of the body, the optimal trajectory of the center of mass (CoM) for the transition from standing to crawling is obtained. By constructing and solving an optimization problem regarding the posture and motion trajectories of the underactuated model, the robot achieves a smooth transition from crawling to standing. In experiments, the wheel-legged robot successfully transitioned between the crawling mode and the upright balanced moving mode and flexibly passed a low and narrow passage. Consequently, the effectiveness of the control strategies and algorithms proposed in this paper are verified by experiments. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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17 pages, 4119 KiB  
Article
Robust Walking for Humanoid Robot Based on Divergent Component of Motion
by Zhao Zhang, Lei Zhang, Shan Xin, Ning Xiao and Xiaoyan Wen
Micromachines 2022, 13(7), 1095; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13071095 - 11 Jul 2022
Cited by 3 | Viewed by 1564
Abstract
In order to perform various complex tasks in place of humans, humanoid robots should walk robustly in the presence of interference. In the paper, an improved model predictive control (MPC) method based on the divergent components of motion (DCM) is proposed. Firstly, the [...] Read more.
In order to perform various complex tasks in place of humans, humanoid robots should walk robustly in the presence of interference. In the paper, an improved model predictive control (MPC) method based on the divergent components of motion (DCM) is proposed. Firstly, the humanoid robot model is simplified to a finite-sized foot-pendulum model. Then, the gait of the humanoid robot in the single-support phase (SSP) and double-support phase (DSP) is planned based on DCM. The center of mass (CoM) of the robot will converge to the DCM, which simplifies the feedback control process. Finally, an MPC controller incorporating an extended Kalman filter (EKF) is proposed to realize the tracking of the desired DCM trajectory. By adjusting the step duration, the controller can compensate for CoM trajectory errors caused by disturbances. Simulation results show that—compared with the traditional method—the method we propose achieves improvements in both disturbed walking and uneven-terrain walking. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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13 pages, 3512 KiB  
Article
Field Programmable Gate Array Based Torque Predictive Control for Permanent Magnet Servo Motors
by Zheng Sun, Yikun Xu, Zhipeng Ma, Jun Xu, Tao Zhang, Muxun Xu and Xuesong Mei
Micromachines 2022, 13(7), 1055; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13071055 - 30 Jun 2022
Cited by 2 | Viewed by 1438
Abstract
With the increasing demand for legged robots, the importance of the joint drive is increasing. The dynamic performance of the inner-most torque/current control loop conditions the capabilities of the whole joint system. In this paper, a direct torque control based on a prediction [...] Read more.
With the increasing demand for legged robots, the importance of the joint drive is increasing. The dynamic performance of the inner-most torque/current control loop conditions the capabilities of the whole joint system. In this paper, a direct torque control based on a prediction model is proposed. The motor torque is estimated by considering calculation and measurement delay; error estimation and torque tracking error are observed and compensated. The control algorithm was implemented on a Field Programmable Gate Array (FPGA) board to apply the capabilities of concurrency calculation of the FPGA. The effectiveness of the proposed control algorithm was experimentally verified. Compared with the commonly used Field Oriented Control (FOC) current controller, the presented controller can not only improve the dynamic performance of the motor but also reduce the average switching times of the inverter. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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13 pages, 16503 KiB  
Article
Design and Joint Position Control of Bionic Jumping Leg Driven by Pneumatic Artificial Muscles
by Zhenhao Dai, Jinjun Rao, Zili Xu and Jingtao Lei
Micromachines 2022, 13(6), 827; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13060827 - 26 May 2022
Cited by 3 | Viewed by 2212
Abstract
Using the skeletal structure and muscle distribution of the hind limbs of a jumping kangaroo as inspiration, a bionic jumping leg was designed with pneumatic artificial muscles (PAMs) as actuators. Referring to the position of biarticular muscles in kangaroos, we constructed a bionic [...] Read more.
Using the skeletal structure and muscle distribution of the hind limbs of a jumping kangaroo as inspiration, a bionic jumping leg was designed with pneumatic artificial muscles (PAMs) as actuators. Referring to the position of biarticular muscles in kangaroos, we constructed a bionic joint using biarticular and monoarticular muscle arrangements. At the same time, the problem of the joint rotation angle limitations caused by PAM shrinkage was solved, and the range of motion of the bionic joint was improved. Based on the output force model of the PAM, we established a dynamic model of the bionic leg using the Lagrange method. In view of the coupling problem caused by the arrangement of the biarticular muscle, an extended state observer was used for decoupling. The system was decoupled into two single-input and single-output systems, and angle tracking control was carried out using active disturbance rejection control (ADRC). The simulation and experimental results showed that the ADRC algorithm had a better decoupling effect and shorter adjustment time than PID control. The jumping experiments showed that the bionic leg could jump with a horizontal displacement of 320 mm and a vertical displacement of 150 mm. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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16 pages, 4870 KiB  
Article
Modeling and Control of a Wheeled Biped Robot
by Zemin Cui, Yaxian Xin, Shuyun Liu, Xuewen Rong and Yibin Li
Micromachines 2022, 13(5), 747; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13050747 - 08 May 2022
Cited by 4 | Viewed by 2949
Abstract
It is difficult to realize the stable control of a wheeled biped robot (WBR), as it is an underactuated nonlinear system. To improve the balance and dynamic locomotion capabilities of a WBR, a decoupled control framework is proposed. First, the WBR is decoupled [...] Read more.
It is difficult to realize the stable control of a wheeled biped robot (WBR), as it is an underactuated nonlinear system. To improve the balance and dynamic locomotion capabilities of a WBR, a decoupled control framework is proposed. First, the WBR is decoupled into a variable-length wheeled inverted pendulum and a five-link multi-rigid body system. Then, for the above two simplified models, a time-varying linear quadratic regulator and a model predictive controller are designed, respectively. In addition, in order to improve the accuracy of the feedback information of the robot, the Kalman filter is used to optimally estimate the system state. The control framework can enable the WBR to realize changing height, resisting external disturbances, velocity tracking and jumping. The results obtained by simulations and physical experiments verify the effectiveness of the framework. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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30 pages, 11287 KiB  
Article
Path Planning Algorithm for Multi-Locomotion Robot Based on Multi-Objective Genetic Algorithm with Elitist Strategy
by Chong Liu, Aizun Liu, Ruchao Wang, Haibin Zhao and Zhiguo Lu
Micromachines 2022, 13(4), 616; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13040616 - 14 Apr 2022
Cited by 12 | Viewed by 2063
Abstract
The multi-locomotion robot (MLR), including bionic insect microrobot, bionic animal robot and so on, should choose different locomotion modes according to the obstacles it faces. However, under different locomotion modes, the power consumption, moving speed, and falling risk of MLR are different, and [...] Read more.
The multi-locomotion robot (MLR), including bionic insect microrobot, bionic animal robot and so on, should choose different locomotion modes according to the obstacles it faces. However, under different locomotion modes, the power consumption, moving speed, and falling risk of MLR are different, and in most cases, they are mutually exclusive. This paper proposes a path planning algorithm for MLR based on a multi-objective genetic algorithm with elitist strategy (MLRMOEGA), which has four optimization objectives: power consumption, time consumption, path falling risk, and path smoothness. We propose two operators: a map analysis operator and a population diversity expansion operator, to improve the global search ability of the algorithm and solve the problem so that it is easy to fall into the local optimal solution. We conduct simulations on MATLAB, and the results show that the proposed algorithm can effectively optimize the objective function value compared with the traditional genetic algorithm under the equal weight of the four optimization objectives, and, under alternative weights, the proposed algorithm can effectively generate the corresponding path of the decision maker’s intention under the weight of preference. Compared with the traditional genetic algorithm, the global search ability is improved effectively. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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18 pages, 696 KiB  
Article
Cyborg Moth Flight Control Based on Fuzzy Deep Learning
by Xiao Yang, Xun-Lin Jiang, Zheng-Lian Su and Ben Wang
Micromachines 2022, 13(4), 611; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13040611 - 13 Apr 2022
Cited by 4 | Viewed by 2187
Abstract
Cyborg insect control methods can be divided into invasive methods and noninvasive methods. Compared to invasive methods, noninvasive methods are much easier to implement, but they are sensitive to complex and highly uncertain environments, for which classical control methods often have low control [...] Read more.
Cyborg insect control methods can be divided into invasive methods and noninvasive methods. Compared to invasive methods, noninvasive methods are much easier to implement, but they are sensitive to complex and highly uncertain environments, for which classical control methods often have low control accuracy. In this paper, we present a noninvasive approach for cyborg moths stimulated by noninvasive ultraviolet (UV) rays. We propose a fuzzy deep learning method for cyborg moth flight control, which consists of a Behavior Learner and a Control Learner. The Behavior Learner is further divided into three hierarchies for learning the species’ common behaviors, group-specific behaviors, and individual-specific behaviors step by step to produce the expected flight parameters. The Control Learner learns how to set UV ray stimulation to make a moth exhibit the expected flight behaviors. Both the Control Learner and Behavior Learner (including its sub-learners) are constructed using a Pythagorean fuzzy denoising autoencoder model. Experimental results demonstrate that the proposed approach achieves significant performance advantages over the state-of-the-art approaches and obtains a high control success rate of over 83% for flight parameter control. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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11 pages, 1692 KiB  
Article
Human–Machine Multi-Turn Language Dialogue Interaction Based on Deep Learning
by Xianxin Ke, Ping Hu, Chenghao Yang and Renbao Zhang
Micromachines 2022, 13(3), 355; https://0-doi-org.brum.beds.ac.uk/10.3390/mi13030355 - 23 Feb 2022
Cited by 3 | Viewed by 2355
Abstract
During multi-turn dialogue, with the increase in dialogue turns, the difficulty of intention recognition and the generation of the following sentence reply become more and more difficult. This paper mainly optimizes the context information extraction ability of the Seq2Seq Encoder in multi-turn dialogue [...] Read more.
During multi-turn dialogue, with the increase in dialogue turns, the difficulty of intention recognition and the generation of the following sentence reply become more and more difficult. This paper mainly optimizes the context information extraction ability of the Seq2Seq Encoder in multi-turn dialogue modeling. We fuse the historical dialogue information and the current input statement information in the encoder to capture the context dialogue information better. Therefore, we propose a BERT-based fusion encoder ProBERT-To-GUR (PBTG) and an enhanced ELMO model 3-ELMO-Attention-GRU (3EAG). The two models mainly enhance the contextual information extraction capability of multi-turn dialogue. To verify the effectiveness of the two proposed models, we demonstrate the effectiveness of our model by combining data based on the LCCC-large multi-turn dialogue dataset and the Naturalconv multi-turn dataset. The experimental comparison results show that, in the multi-turn dialogue experiments of the open domain and fixed topic, the two Seq2Seq coding models proposed are significantly improved compared with the current state-of-the-art models. For specified topic multi-turn dialogue, the 3EAG model has the average BLEU value reaches the optimal 32.4, which achieves the best language generation effect, and the BLEU value in the actual dialogue verification experiment also surpasses 31.8. for open-domain multi-turn dialogue. The average BLEU value of the PBTG model reaches 31.8, the optimal 31.8 achieves the best language generation effect, and the BLEU value in the actual dialogue verification experiment surpasses 31.2. So, the 3EAG model is more suitable for fixed-topic multi-turn dialogues for the two tasks. The PBTG model is more muscular in open-domain multi-turn dialogue tasks; therefore, our model is significant for promoting multi-turn dialogue research. Full article
(This article belongs to the Special Issue New Advances in Biomimetic Robots)
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