Trends and Prospects in Biorobotics

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

Deadline for manuscript submissions: closed (15 November 2021) | Viewed by 3070

Special Issue Editor


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Guest Editor
1. Research & Training Area, INAIL Prosthetic Centre, 40054 Budrio (BO), Italy
2. University of Bologna, 40124 Bologna, Italy
Interests: upper and lower limb prostheses; technological aids; home automation; bioengineering

Special Issue Information

Dear Colleagues,

When was the first bionic human born?

Every 10 years or so, cyclically in the media, there is the birth of “new” bionic human, thanks to innovations in sectors such as electronics, computer science, mechanics, new materials in the prosthetic field, which lead to the appearance of new components and thus the birth of a “new first bionic man”. To date, however, despite the gradual steps forward, from a functional point of view, we are still very far from the performance of natural limbs. In fact, to have a “true bionic man”, it is not enough to have new devices that are increasingly performing with small and artificial intelligence functionality; in order to have a real embodiment, our brain must consider an artificial limb as a natural limb, and therefore, we must use the same language for all parts of the body, whether natural or artificial. In this field, little progress has been made in the prosthetic field in recent decades; in fact, almost all prosthetic devices still use myoelectric signals as a human–machine interface, which are unidirectional and therefore able to transmit commands to the prosthesis, but not to receive sensory information. It is thanks to the sensorial feedback that complete integration of the prosthetic device is obtained; it is therefore a matter of moving from the use of myoelectric signals to neuro electric signals, using both efferent and afferent fibers. It is certainly a very complex issue on which it is still important to invest in research, and the idea of ​​a few decades ago to create a “neural connector” capable of bi-directionally interfacing an electronic device with a nerve is still very topical. Research is important, but the role of the companies that have to fill the gap between the research and the final user is fundamental, as only through them can an experimental device be produced on a large scale and will it bring real benefits for disabled people. To achieve this, companies have to be more involved in research from the very first experiments so that they can give their contribution in terms of feasibility and sustainability of the whole process.

Dr. Angelo Davalli
Guest Editor

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Keywords

  • prosthetics
  • neural feedback
  • bionic
  • rehabilitation team
  • embodiment
  • companies’ engagement

Published Papers (1 paper)

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Research

28 pages, 8662 KiB  
Article
Synchronized Motion Profiles for Inverse-Dynamics-Based Online Control of Three Inextensible Segments of Trunk-Type Robot Actuators
by Mindaugas Matukaitis, Renaldas Urniezius, Deividas Masaitis, Lukas Zlatkus, Benas Kemesis and Gintaras Dervinis
Appl. Sci. 2021, 11(7), 2946; https://0-doi-org.brum.beds.ac.uk/10.3390/app11072946 - 25 Mar 2021
Cited by 1 | Viewed by 2646
Abstract
This study proposes a novel method for the positioning and spatial orientation control of three inextensible segments of trunk-type robots. The suggested algorithm imposes a soft constraint assumption for the end-effector’s endpoint and a mandatory constraint on its direction. Simultaneously, the algorithm by-design [...] Read more.
This study proposes a novel method for the positioning and spatial orientation control of three inextensible segments of trunk-type robots. The suggested algorithm imposes a soft constraint assumption for the end-effector’s endpoint and a mandatory constraint on its direction. Simultaneously, the algorithm by-design enforces nonholonomic features on the robot segments in the form of arcs. An approximate robot spine curve is the key to the final robot state configuration based on the given conditions. The numeric simulation showed acceptable (less than 1 s) performance for single-core processing tasks. The parametric method finds the best proximate robot state solution and represents the gray box model in addition to existing learning or black-box inverse dynamics approaches. This study also shows that a multiple inverse kinematics answer constructs a single inverse dynamics solution that defines the robot actuators’ motion profiles, synchronized in time. Finally, this text presents rotational expressions and their outlines for controlling the manipulator’s tendons. Full article
(This article belongs to the Special Issue Trends and Prospects in Biorobotics)
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