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18 pages, 3041 KiB

Open AccessArticle

Experimental Investigation of a Cable Robot Recovery Strategy

by Giovanni Boschetti, Riccardo Minto and Alberto Trevisani

Robotics 2021, 10(1), 35; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics10010035 - 16 Feb 2021

Cited by 7 | Viewed by 4593

Developing an emergency procedure for cable-driven parallel robots is not a trivial process, since it is not possible to halt the end-effector by quickly braking the actuators as in rigid-link manipulators. For this reason, the cable robot recovery strategy is an important topic [...] Read more.

Developing an emergency procedure for cable-driven parallel robots is not a trivial process, since it is not possible to halt the end-effector by quickly braking the actuators as in rigid-link manipulators. For this reason, the cable robot recovery strategy is an important topic of research, and the literature provides several approaches. However, the computational efficiency of the recovery algorithm is fundamental for real-time applications. Thus, this paper presents a recovery strategy adopted in an experimental setup consisting of a three degrees-of-freedom (3-DOF) suspended cable robot controlled by an industrial PC. The presentation of the used control system lists the industrial-grade components installed, further highlighting the industrial implication of the work. Lastly, the experimental validation of the recovery strategy proves the effectiveness of the work. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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29 pages, 3233 KiB

Open AccessArticle

FloorVLoc: A Modular Approach to Floorplan Monocular Localization

by John Noonan, Ehud Rivlin and Hector Rotstein

Robotics 2020, 9(3), 69; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9030069 - 10 Sep 2020

Cited by 2 | Viewed by 3214

Abstract

Intelligent vehicles for search and rescue, whose mission is assisting emergency personnel by visually exploring an unfamiliar building, require accurate localization. With GPS not available, and approaches relying on new infrastructure installation, artificial landmarks, or pre-constructed dense 3D maps not feasible, the question [...] Read more.

Intelligent vehicles for search and rescue, whose mission is assisting emergency personnel by visually exploring an unfamiliar building, require accurate localization. With GPS not available, and approaches relying on new infrastructure installation, artificial landmarks, or pre-constructed dense 3D maps not feasible, the question is whether there is an approach which can combine ubiquitous prior map information with a monocular camera for accurate positioning. Enter FloorVLoc—Floorplan Vision Vehicle Localization. We provide a means to integrate a monocular camera with a floorplan in a unified and modular fashion so that any monocular visual Simultaneous Localization and Mapping (SLAM) system can be seamlessly incorporated for global positioning. Using a floorplan is especially beneficial since walls are geometrically stable, the memory footprint is low, and prior map information is kept at a minimum. Furthermore, our theoretical analysis of the visual features associated with the walls shows how drift is corrected. To see this approach in action, we developed two full global positioning systems based on the core methodology introduced, operating in both Monte Carlo Localization and linear optimization frameworks. Experimental evaluation of the systems in simulation and a challenging real-world environment demonstrates that FloorVLoc performs with an average error of 0.06 m across 80 m in real-time. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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11 pages, 749 KiB

Open AccessCommunication

Is Artificial Man Still Far Away: Anthropomimetic Robots Versus Robomimetic Humans

by Veljko Potkonjak

Robotics 2020, 9(3), 57; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9030057 - 24 Jul 2020

Cited by 6 | Viewed by 7920

Abstract

The article presents a viewpoint on the current status and limitations of humanoid robotics and possible future progress. It may be seen as a continuation of the article “How far away is artificial man?” published in 2001 by a group of authors, among [...] Read more.

The article presents a viewpoint on the current status and limitations of humanoid robotics and possible future progress. It may be seen as a continuation of the article “How far away is artificial man?” published in 2001 by a group of authors, among them the author of the present text, in IEEE Robotics &Automation Magazine (IEEE RAM). The previous article defined three key aspects of advanced humanoids, namely human-like shape and motion, intelligence, and communication. The current article discusses the situation 18 years later and takes note of the trend towards biologically inspired solutions to technical problems. It might appear to put forward controversial ideas, but the author believes they are realistic observations and constitute a frank presentation of apparent tendencies. The author argues that the crucial breakthrough towards an “artificial man” has not yet been made, as formidable challenges remain and cannot be overcome easily in the near future. On the other hand, the question arises: After unsuccessful attempts to solve robotic problems by designing technical systems that increasingly imitate humans, can we finally drop out of engineering and completely turn to biology and look for solutions there? This controversial idea means artificial creation and mass production of human beings that behave like robots, i.e., robomimetic humans. The article is a brief reality check of this concept. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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14 pages, 4145 KiB

Open AccessArticle

Finite Element Modeling in the Design Process of 3D Printed Pneumatic Soft Actuators and Sensors

by Charbel Tawk and Gursel Alici

Robotics 2020, 9(3), 52; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9030052 - 07 Jul 2020

Cited by 51 | Viewed by 9313

Abstract

The modeling of soft structures, actuators, and sensors is challenging, primarily due to the high nonlinearities involved in such soft robotic systems. Finite element modeling (FEM) is an effective technique to represent soft and deformable robotic systems containing geometric nonlinearities due to large [...] Read more.

The modeling of soft structures, actuators, and sensors is challenging, primarily due to the high nonlinearities involved in such soft robotic systems. Finite element modeling (FEM) is an effective technique to represent soft and deformable robotic systems containing geometric nonlinearities due to large mechanical deformations, material nonlinearities due to the inherent nonlinear behavior of the materials (i.e., stress-strain behavior) involved in such systems, and contact nonlinearities due to the surfaces that come into contact upon deformation. Prior to the fabrication of such soft robotic systems, FEM can be used to predict their behavior efficiently and accurately under various inputs and optimize their performance and topology to meet certain design and performance requirements. In this article, we present the implementation of FEM in the design process of directly three-dimensional (3D) printed pneumatic soft actuators and sensors to accurately predict their behavior and optimize their performance and topology. We present numerical and experimental results to show that this approach is very effective to rapidly and efficiently design the soft actuators and sensors to meet certain design requirements and to save time, modeling, design, and fabrication resources. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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30 pages, 25522 KiB

Open AccessArticle

Learning Sequential Force Interaction Skills

by Simon Manschitz, Michael Gienger, Jens Kober and Jan Peters

Robotics 2020, 9(2), 45; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9020045 - 17 Jun 2020

Cited by 9 | Viewed by 4673

Abstract

Learning skills from kinesthetic demonstrations is a promising way of minimizing the gap between human manipulation abilities and those of robots. We propose an approach to learn sequential force interaction skills from such demonstrations. The demonstrations are decomposed into a set of movement [...] Read more.

Learning skills from kinesthetic demonstrations is a promising way of minimizing the gap between human manipulation abilities and those of robots. We propose an approach to learn sequential force interaction skills from such demonstrations. The demonstrations are decomposed into a set of movement primitives by inferring the underlying sequential structure of the task. The decomposition is based on a novel probability distribution which we call Directional Normal Distribution. The distribution allows infering the movement primitive’s composition, i.e., its coordinate frames, control variables and target coordinates from the demonstrations. In addition, it permits determining an appropriate number of movement primitives for a task via model selection. After finding the task’s composition, the system learns to sequence the resulting movement primitives in order to be able to reproduce the task on a real robot. We evaluate the approach on three different tasks, unscrewing a light bulb, box stacking and box flipping. All tasks are kinesthetically demonstrated and then reproduced on a Barrett WAM robot. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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17 pages, 2343 KiB

Open AccessArticle

User Affect Elicitation with a Socially Emotional Robot

by Mingyang Shao, Matt Snyder, Goldie Nejat and Beno Benhabib

Robotics 2020, 9(2), 44; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9020044 - 03 Jun 2020

Cited by 15 | Viewed by 4805

Abstract

To effectively communicate with people, social robots must be capable of detecting, interpreting, and responding to human affect during human–robot interactions (HRIs). In order to accurately detect user affect during HRIs, affect elicitation techniques need to be developed to create and train appropriate [...] Read more.

To effectively communicate with people, social robots must be capable of detecting, interpreting, and responding to human affect during human–robot interactions (HRIs). In order to accurately detect user affect during HRIs, affect elicitation techniques need to be developed to create and train appropriate affect detection models. In this paper, we present such a novel affect elicitation and detection method for social robots in HRIs. Non-verbal emotional behaviors of the social robot were designed to elicit user affect, which was directly measured through electroencephalography (EEG) signals. HRI experiments with both younger and older adults were conducted to evaluate our affect elicitation technique and compare the two types of affect detection models we developed and trained utilizing multilayer perceptron neural networks (NNs) and support vector machines (SVMs). The results showed that; on average, the self-reported valence and arousal were consistent with the intended elicited affect. Furthermore, it was also noted that the EEG data obtained could be used to train affect detection models with the NN models achieving higher classification rates Full article

(This article belongs to the Special Issue Feature Papers 2020)

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Review

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29 pages, 29107 KiB

Open AccessReview

Advances in Finger and Partial Hand Prosthetic Mechanisms

by Erasmo Difonzo, Giovanni Zappatore, Giacomo Mantriota and Giulio Reina

Robotics 2020, 9(4), 80; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9040080 - 01 Oct 2020

Cited by 6 | Viewed by 10413

Abstract

Approximately 70% of the upper extremity amputations refers to partial hand loss with the involvement of one or more fingers. Historically, this type of limb amputation has been addressed adopting simple opposition designs that use the movement of the residual digit for grasping [...] Read more.

Approximately 70% of the upper extremity amputations refers to partial hand loss with the involvement of one or more fingers. Historically, this type of limb amputation has been addressed adopting simple opposition designs that use the movement of the residual digit for grasping against a fixed device. Nevertheless, in the last few years, technological advances, and the introduction of modern computer-aided tools for the synthesis and functional design of mechanisms have led to the development of smaller, more robust systems that are constantly improving body-powered and electrically-powered prototypes. This paper surveys cutting-edge solutions proposed in research or available on the market for single finger or partial hand prostheses. First, the main design requirements are outlined. Then, a wide number of prototypes are detailed underlying advantages and drawbacks. The overall goal is to create a solid starting point for the study and development of the next generation of prostheses that can be developed to advance the current state-of-the-art. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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18 pages, 5961 KiB

Open AccessReview

A Survey on Mechanical Solutions for Hybrid Mobile Robots

by Matteo Russo and Marco Ceccarelli

Robotics 2020, 9(2), 32; https://0-doi-org.brum.beds.ac.uk/10.3390/robotics9020032 - 08 May 2020

Cited by 21 | Viewed by 7653

Abstract

This paper presents a survey on mobile robots as systems that can move in different environments with walking, flying and swimming up to solutions that combine those capabilities. The peculiarities of these mobile robots are analyzed with significant examples as references and a [...] Read more.

This paper presents a survey on mobile robots as systems that can move in different environments with walking, flying and swimming up to solutions that combine those capabilities. The peculiarities of these mobile robots are analyzed with significant examples as references and a specific case study is presented as from the direct experiences of the authors for the robotic platform HeritageBot, in applications within the frame of Cultural Heritage. The hybrid design of mobile robots is explained as integration of different technologies to achieve robotic systems with full mobility. Full article

(This article belongs to the Special Issue Feature Papers 2020)

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