Special Issue "Biorobotics and Bionic Systems"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 31 July 2021.

Special Issue Editor

Dr. Donato Romano
Website
Guest Editor
The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa
Interests: applied biology; biorobotics; biohybrid systems; neuroethology; ethorobotics; zoology

Special Issue Information

Dear Colleagues,

The increasingly complex and wide use of robots is driving a growing number of scientists to investigate and understand processes and mechanisms evolved by living organisms to face particular problems in order to reproduce these strategies in artificial agents.

These agents are far from traditional robots used in industry that are programmed to fulfill specific tasks in structured environments.

Biorobotics and bionics are relatively young scientific and technological fields that include several disciplines such as robotics, biology, medicine, micro-nanotechnology, and artificial intelligence.

Bioinspired robots and bionic systems have a broad range of applications, including the exploration of hostile/hazardous environments for humans; the employment in disaster scenarios; or the use as service/social robots to improve the quality of life, such as prostheses, rehabilitation equipment, and assistive tools.

This Special Issue welcomes original research and review articles that cover, but are not limited to:

  • Biomimetic and bioinspired artifacts;
  • Biohybrid systems;
  • Biomechanics;
  • Bionic sensors;
  • Micro-electromechanical systems;
  • Multi-agent systems;
  • Neuro-robotics;
  • Soft robotics;
  • Swarm intelligence.

Dr. Donato Romano
Guest Editor

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 papers will be 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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2000 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

  • bioinspiration
  • biomimetics
  • bionics
  • biorobotics
  • biology
  • intelligence
  • biohybrid system

Published Papers (4 papers)

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Research

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Open AccessFeature PaperArticle
Wankelmut: A Simple Benchmark for the Evolvability of Behavioral Complexity
Appl. Sci. 2021, 11(5), 1994; https://doi.org/10.3390/app11051994 - 24 Feb 2021
Abstract
In evolutionary robotics, an encoding of the control software that maps sensor data (input) to motor control values (output) is shaped by stochastic optimization methods to complete a predefined task. This approach is assumed to be beneficial compared to standard methods of controller [...] Read more.
In evolutionary robotics, an encoding of the control software that maps sensor data (input) to motor control values (output) is shaped by stochastic optimization methods to complete a predefined task. This approach is assumed to be beneficial compared to standard methods of controller design in those cases where no a priori model is available that could help to optimize performance. For robots that have to operate in unpredictable environments as well, an evolutionary robotics approach is favorable. We present here a simple-to-implement, but hard-to-pass benchmark to allow for quantifying the “evolvability” of such evolving robot control software towards increasing behavioral complexity. We demonstrate that such a model-free approach is not a free lunch, as already simple tasks can be unsolvable barriers for fully open-ended uninformed evolutionary computation techniques. We propose the “Wankelmut” task as an objective for an evolutionary approach that starts from scratch without pre-shaped controller software or any other informed approach that would force the behavior to be evolved in a desired way. Our main claim is that “Wankelmut” represents the simplest set of problems that makes plain-vanilla evolutionary computation fail. We demonstrate this by a series of simple standard evolutionary approaches using different fitness functions and standard artificial neural networks, as well as continuous-time recurrent neural networks. All our tested approaches failed. From our observations, we conclude that other evolutionary approaches will also fail if they do not per se favor or enforce the modularity of the evolved structures and if they do not freeze or protect already evolved functionalities from being destroyed again in the later evolutionary process. However, such a protection would require a priori knowledge of the solution of the task and contradict the “no a priori model” approach that is often claimed in evolutionary computation. Thus, we propose a hard-to-pass benchmark in order to make a strong statement for self-complexifying and generative approaches in evolutionary computation in general and in evolutionary robotics specifically. We anticipate that defining such a benchmark by seeking the simplest task that causes the evolutionary process to fail can be a valuable benchmark for promoting future development in the fields of artificial intelligence, evolutionary robotics, and artificial life. Full article
(This article belongs to the Special Issue Biorobotics and Bionic Systems)
Open AccessArticle
Controllable Height Hopping of a Parallel Legged Robot
Appl. Sci. 2021, 11(4), 1421; https://doi.org/10.3390/app11041421 - 04 Feb 2021
Abstract
Legged robots imitating animals have become versatile and applicable in more application scenarios recent years. Most of their functions rely on powerful athletic abilities, which require the robots to have remarkable actuator capacities and controllable dynamic performance. In most experimental demonstrations, continuous hopping [...] Read more.
Legged robots imitating animals have become versatile and applicable in more application scenarios recent years. Most of their functions rely on powerful athletic abilities, which require the robots to have remarkable actuator capacities and controllable dynamic performance. In most experimental demonstrations, continuous hopping at a desired height is a basic required motion for legged robots to verify their athletic ability. However, recent legged robots have limited ability in balance of high torque output and actuator transparency and appropriate structure size at the same time. Therefore, in our research, we developed a parallel robot leg using a brushless direct current motor combined with a harmonic driver, without extra force or torque sensor feedback, which uses virtual model control (VMC) to realize active compliance on the leg, and a whole-leg control system with dynamics modeling and parameter optimization for continuous vertical hopping at a desired height. In our experiments, the robot was able to maintain stability during vertical hopping while following a variable reference height in various ground situations. Full article
(This article belongs to the Special Issue Biorobotics and Bionic Systems)
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Open AccessArticle
Mechanical Design of a Bioinspired Compliant Robotic Wrist Rehabilitation Equipment
Appl. Sci. 2021, 11(3), 1246; https://doi.org/10.3390/app11031246 - 29 Jan 2021
Abstract
Early social reintegration of patients with disabilities of the wrist is possible with the help of dedicated rehabilitation equipment. Using such equipment reduces the duration of recovery and reduces significantly rehabilitation costs. Based on these considerations the paper puts forward a novel constructive [...] Read more.
Early social reintegration of patients with disabilities of the wrist is possible with the help of dedicated rehabilitation equipment. Using such equipment reduces the duration of recovery and reduces significantly rehabilitation costs. Based on these considerations the paper puts forward a novel constructive solution of rehabilitation equipment that ensures the simultaneous passive mobilization of the radiocarpal, metacarpophalangeal, and interphalangeal joints. The novelty of this equipment consists in the bioinspired concept of the hand support based on the Fin-Ray effect and in driving it by means of a pneumatic muscle, an inherently compliant actuator. The paper places an emphasis on the compliant character of the rehabilitation equipment that is responsible for its adaptability to the concrete conditions of patient pain tolerability. Full article
(This article belongs to the Special Issue Biorobotics and Bionic Systems)
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Review

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Open AccessReview
Jumping Locomotion Strategies: From Animals to Bioinspired Robots
Appl. Sci. 2020, 10(23), 8607; https://doi.org/10.3390/app10238607 - 01 Dec 2020
Cited by 1
Abstract
Jumping is a locomotion strategy widely evolved in both invertebrates and vertebrates. In addition to terrestrial animals, several aquatic animals are also able to jump in their specific environments. In this paper, the state of the art of jumping robots has been systematically [...] Read more.
Jumping is a locomotion strategy widely evolved in both invertebrates and vertebrates. In addition to terrestrial animals, several aquatic animals are also able to jump in their specific environments. In this paper, the state of the art of jumping robots has been systematically analyzed, based on their biological model, including invertebrates (e.g., jumping spiders, locusts, fleas, crickets, cockroaches, froghoppers and leafhoppers), vertebrates (e.g., frogs, galagoes, kangaroos, humans, dogs), as well as aquatic animals (e.g., both invertebrates and vertebrates, such as crabs, water-striders, and dolphins). The strategies adopted by animals and robots to control the jump (e.g., take-off angle, take-off direction, take-off velocity and take-off stability), aerial righting, land buffering, and resetting are concluded and compared. Based on this, the developmental trends of bioinspired jumping robots are predicted. Full article
(This article belongs to the Special Issue Biorobotics and Bionic Systems)
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