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Biomimetics
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Bio-Inspired Locomotion and Manipulation of Legged Robot
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Bio-Inspired Locomotion and Manipulation of Legged Robot

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: closed (25 December 2023) | Viewed by 8736

Special Issue Editors

Prof. Dr. Xuechao Chen

E-Mail Website
Guest Editor
Beijing Institute of Technology, Beijing, China
Interests: bio-inspired robotics; legged robot locomotion; trajectory planning and control
Special Issues, Collections and Topics in MDPI journals
Dr. Gan Ma

E-Mail Website
Guest Editor
Sino-German College of Intelligent Manufacturing, Shenzhen Technology University, Shenzhen, China
Interests: humanoid robots; motion planning; robotics; mechatronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Biomimetic technologies have been widely used to promote the development of robot technology, in which the legged robot based on bionic characteristics plays an important role in replacing or assisting human beings to complete tasks in complex and uncertain environments. In order to improve its application capability, the legged robot has to deal with real-world challenges, such as perception, manipulation and balance control in unstructured environments.

This Special Issue on the “Bio-Inspired Locomotion and Manipulation of Legged Robot” aims to showcase new research achievements, findings, and ideas in the field of bio-inspired legged robots, such as the perception of legged robots, the study of human-like manipulation, the proposal of stable and robust control methods machine learning, and so on. To this end, we encourage the submissions of papers with new advances in theoretical, experimental, and computational approaches to bionic legged robot applications. We call for contributions from researchers in all realms of bio-inspired locomotion and manipulation of legged robots.

Prof. Dr. Xuechao Chen
Dr. Gan Ma
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. Biomimetics 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 2200 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

  • bio-inspired legged robot design
  • modeling and optimization
  • robotic manipulation
  • robot dynamics
  • motion control
  • navigation
  • machine learning
  • motion planning
  • bionic legged robot system
  • perception and sensing

Published Papers (6 papers)

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Research

20 pages, 2353 KiB  
Article
Design of Low-Cost Modular Bio-Inspired Electric–Pneumatic Actuator (EPA)-Driven Legged Robots
by Alessandro Brugnera Silva, Marc Murcia, Omid Mohseni, Ryu Takahashi, Arturo Forner-Cordero, Andre Seyfarth, Koh Hosoda and Maziar Ahmad Sharbafi
Biomimetics 2024, 9(3), 164; https://doi.org/10.3390/biomimetics9030164 - 07 Mar 2024
Viewed by 1243
Abstract
Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion [...] Read more.
Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in electric–pneumatic actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monoped robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, (1) provide opportunities to study different locomotor subfunctions—stance, swing, and balance; (2) help investigate the role of actuation schemes in tasks such as hopping and walking; and (3) allow testing hypotheses regarding biological locomotors in real-world physical test benches. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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14 pages, 10901 KiB  
Article
Learning Quadrupedal High-Speed Running on Uneven Terrain
by Xinyu Han and Mingguo Zhao
Biomimetics 2024, 9(1), 37; https://doi.org/10.3390/biomimetics9010037 - 05 Jan 2024
Viewed by 1389
Abstract
Reinforcement learning (RL)-based controllers have been applied to the high-speed movement of quadruped robots on uneven terrains. The external disturbances increase as the robot moves faster on such terrains, affecting the stability of the robot. Many existing RL-based methods adopt higher control frequencies [...] Read more.
Reinforcement learning (RL)-based controllers have been applied to the high-speed movement of quadruped robots on uneven terrains. The external disturbances increase as the robot moves faster on such terrains, affecting the stability of the robot. Many existing RL-based methods adopt higher control frequencies to respond quickly to the disturbance, which requires a significant computational cost. We propose a control framework that consists of an RL-based control policy updating at a low frequency and a model-based joint controller updating at a high frequency. Unlike previous methods, our policy outputs the control law for each joint, executed by the corresponding high-frequency joint controller to reduce the impact of external disturbances on the robot. We evaluated our method on various simulated terrains with height differences of up to 6 cm. We achieved a running motion of 1.8 m/s in the simulation using the Unitree A1 quadruped. The RL-based control policy updates at 50 Hz with a latency of 20 ms, while the model-based joint controller runs at 1000 Hz. The experimental results show that the proposed framework can overcome the latency caused by low-frequency updates, making it applicable for real-robot deployment. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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19 pages, 4935 KiB  
Article
Bionic Design and Optimization on the Flow Channel of a Legged Robot Joint Hydraulic Drive Unit Based on Additive Manufacturing
by Zhipeng Huang, Chenhao Du, Chenxu Wang, Qianran Sun, Yuepeng Xu, Lufang Shao, Bin Yu, Guoliang Ma and Xiangdong Kong
Biomimetics 2024, 9(1), 13; https://doi.org/10.3390/biomimetics9010013 - 31 Dec 2023
Cited by 2 | Viewed by 1189
Abstract
The joint hydraulic drive unit (HDU) serves as a pivotal element in enabling the high-performance movements of legged robots. Functioning as the conduit linking the oil source and the actuator, the hydraulic flow channel significantly impacts actuator performance. Hence, optimizing the HDU flow [...] Read more.
The joint hydraulic drive unit (HDU) serves as a pivotal element in enabling the high-performance movements of legged robots. Functioning as the conduit linking the oil source and the actuator, the hydraulic flow channel significantly impacts actuator performance. Hence, optimizing the HDU flow channel becomes imperative, enhancing not only HDU efficiency but also the overall system performance. This paper introduces a novel approach by aligning the hydraulic flow channel of the joint HDU with the arteriovenous layout of the cardiac vascular system, departing from the conventional machining flow channel model. Through simulations determining the optimal range of the vascular branch radius and angle, this study guides the design optimization of the joint HDU flow channel. With the primary optimization goal of reducing pressure loss, the study compares simulation outcomes of various flow channel models—linear, variable excessive radius, and the multidimensional Bessel curve—tailored to suit the arrangement specifics of the joint HDU. Further validating these designs, the flow channels are fabricated using additive manufacturing for experimental verification. The integration of simulation analyses and pressure loss testing reveals a remarkable reduction of over 40% in pressure loss for the bionic flow channel compared to the conventional machining form. This empirical evidence strongly substantiates the bionic flow channel’s superior efficacy in pressure loss reduction. The findings presented herein offer valuable insights for the development of low-loss flow channels in joint HDUs, thereby presenting a new avenue for designing energy-efficient, high power-to-weight ratio legged robots. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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19 pages, 6218 KiB  
Article
A Multi-Agent Reinforcement Learning Method for Omnidirectional Walking of Bipedal Robots
by Haiming Mou, Jie Xue, Jian Liu, Zhen Feng, Qingdu Li and Jianwei Zhang
Biomimetics 2023, 8(8), 616; https://doi.org/10.3390/biomimetics8080616 - 16 Dec 2023
Cited by 1 | Viewed by 1493
Abstract
Achieving omnidirectional walking for bipedal robots is considered one of the most challenging tasks in robotics technology. Reinforcement learning (RL) methods have proved effective in bipedal walking tasks. However, most existing methods use state machines to switch between multiple policies and achieve omnidirectional [...] Read more.
Achieving omnidirectional walking for bipedal robots is considered one of the most challenging tasks in robotics technology. Reinforcement learning (RL) methods have proved effective in bipedal walking tasks. However, most existing methods use state machines to switch between multiple policies and achieve omnidirectional gait, which results in shaking during the policy switching process for bipedal robots. To achieve a seamless transition between omnidirectional gait and transient motion for full-size bipedal robots, we propose a novel multi-agent RL method. Firstly, a multi-agent RL algorithm based on the actor–critic framework is designed, and policy entropy is introduced to improve exploration efficiency. By learning agents with parallel initial state distributions, we minimize reliance on gait planner effectiveness in the Robot Operating System (ROS). Additionally, we design a novel heterogeneous policy experience replay mechanism based on Euclidean distance. Secondly, considering the periodicity of bipedal robot walking, we develop a new periodic gait function. Including periodic objectives in the policy can accelerate the convergence speed of training periodic gait functions. Finally, to enhance the robustness of the policy, we construct a novel curriculum learning method by discretizing Gaussian distribution and incorporate it into the robot’s training task. Our method is validated in a simulation environment, and the results show that our method can achieve multiple gaits through a policy network and achieve smooth transitions between different gaits. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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20 pages, 15315 KiB  
Article
A Hierarchical Control Strategy for a Rigid–Flexible Coupled Hexapod Bio-Robot
by Kuo Yang, Xinhui Liu, Changyi Liu and Xurui Tan
Biomimetics 2023, 8(8), 561; https://doi.org/10.3390/biomimetics8080561 - 21 Nov 2023
Viewed by 1500
Abstract
The motion process of legged robots contains not only rigid-body motion but also flexible motion with elastic deformation of the legs, especially for heavy loads. Hence, the characteristics of the flexible components and their interactions with the rigid components need to be considered. [...] Read more.
The motion process of legged robots contains not only rigid-body motion but also flexible motion with elastic deformation of the legs, especially for heavy loads. Hence, the characteristics of the flexible components and their interactions with the rigid components need to be considered. In this paper, a hierarchical control strategy for robots with rigid–flexible coupling characteristics is proposed. This strategy involves (1) leg force prediction based on real-time motion trajectories and feedforward compensation for the error caused by flexible components; (2) building upon the centroid dynamics model of the rigid-body chassis, the centroid trajectories (centroid angular momentum (CAM) and centroid linear momentum (CLM)) and the body trajectory are taken into account to derive the optimal drive torque for maintaining body stability; (3) finally, the precise force control of the hydraulic drive units is achieved through the sliding mode control algorithm, integrating the dynamic model of the flexible legs. The proposed methods are validated on a giant hexapod robot weighing 3.5 tons, demonstrating that the introduced approach can reduce the robot’s vibrations. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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14 pages, 2677 KiB  
Article
Using Footpad Sculpturing to Enhance the Maneuverability and Speed of a Robotic Marangoni Surfer
by Samuel Bechard, Mitchel L. Timm, Hassan Masoud and Jonathan P. Rothstein
Biomimetics 2023, 8(5), 440; https://doi.org/10.3390/biomimetics8050440 - 20 Sep 2023
Viewed by 959
Abstract
From insects to arachnids to bacteria, the surfaces of lakes and ponds are teaming with life. Many modes of locomotion are employed by these organisms to navigate along the air–water interface, including the use of lipid-laden excretions that can locally change the surface [...] Read more.
From insects to arachnids to bacteria, the surfaces of lakes and ponds are teaming with life. Many modes of locomotion are employed by these organisms to navigate along the air–water interface, including the use of lipid-laden excretions that can locally change the surface tension of the water and induce a Marangoni flow. In this paper, we improved the speed and maneuverability of a miniature remote-controlled robot that mimics insect locomotion using an onboard tank of isopropyl alcohol and a series of servomotors to control both the rate and location of alcohol release to both propel and steer the robot across the water. Here, we studied the effect of a series of design changes to the foam rubber footpads, which float the robot and are integral in efficiently converting the alcohol-induced surface tension gradients into propulsive forces and effective maneuvering. Two designs were studied: a two-footpad design and a single-footpad design. In the case of two footpads, the gap between the two footpads was varied to investigate its impact on straight-line speed, propulsion efficiency, and maneuverability. An optimal design was found with a small but finite gap between the two pads of 7.5 mm. In the second design, a single footpad without a central gap was studied. This footpad had a rectangular cut-out in the rear to capture the alcohol. Footpads with wider and shallower cut-outs were found to optimize efficiency. This observation was reinforced by the predictions of a simple theoretical mechanical model. Overall, the optimized single-footpad robot outperformed the two-footpad robot, producing a 30% improvement in speed and a 400% improvement in maneuverability. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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