Special Issue "Human Friendly Robotics"

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: 25 May 2019

Special Issue Editors

Guest Editor
Dr. Fei Chen

Department of Advanced Robotics, Italian Institute of Technology. Via Morego 30, 16163 Genova, Italy
Website | E-Mail
Interests: mobile and dexterous manipulation; collaborative robotics; robot learning
Guest Editor
Dr. Yan Wu

A*STAR Institute for Infocomm Research, 1 Fusionopolis Way #21-01 Connexis (South Tower) 138632, Singapore
Website | E-Mail
Interests: assistive and service robotics, multimodal robot learning and dexterity
Guest Editor
Dr. Alessandro Di Nuovo

Sheffield Robotics & Department of Computing, Sheffield Hallam University, Sheffield, S1 1WB, UK
Website | E-Mail
Interests: cognitive robotics; developmental robotics; human-robot interaction; intelligent robots; machine and deep learning applications
Guest Editor
Dr. Dimitri Ognibene

Department of Computer Science and Electronic Engineering, University of Essex, ColchesterCO4 3SQ, UK
Website | E-Mail
Interests: active perception and adaptation in complex social environments

Special Issue Information

Dear Colleagues,

The growing demand to automate daily tasks using new robotic technologies is driving the development of human-friendly robots, i.e., safe and dependable machines, operating in the close vicinity to humans or directly interacting with them in a wide range of domains. The technological shift from classical industrial robots restricted in cages to collaborative robots that are interacting closely with humans, is facing major challenges that need to be addressed.

To this end, we organize the 11th International Workshop on Human-Friendly Robotics (HFR 2018) on 13–14 November, 2018, in Shenzhen, China. The objective of the workshop is to create a focused single-track workshop and to bring together researchers for sharing knowledge in design, control, safety and ethical issues, concerning the application of robots in everyday life. This Special Issue will collect selected papers from the workshop. Potential contributors to this Special Issue are also encouraged to submit and present in the HFR2018 (more information can be found here: HFR2018.org).

List of Topics

Fundamentals of human-friendly robots: mechatronic design, control, analysis (safety measurements, performance metrics, impedance estimation, etc.)

Applications of human-friendly robots: physical interaction (medical and rehabilitation devices, prostheses and orthoses, telerobotics, etc.), cognitive interaction (robot assisted therapy, personal and entertainment robots, robot learning, etc.),

Social and ethical issues

Dr. Fei Chen
Dr. Yan Wu
Dr. Alessandro Di Nuovo
Dr. Dimitri Ognibene
Guest Editors

Manuscript Submission Information

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Published Papers (10 papers)

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Research

Open AccessArticle
A Robot Learning Method with Physiological Interface for Teleoperation Systems
Appl. Sci. 2019, 9(10), 2099; https://doi.org/10.3390/app9102099 (registering DOI)
Received: 16 December 2018 / Revised: 24 April 2019 / Accepted: 10 May 2019 / Published: 22 May 2019
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Abstract
The human operator largely relies on the perception of remote environmental conditions to make timely and correct decisions in a prescribed task when the robot is teleoperated in a remote place. However, due to the unknown and dynamic working environments, the manipulator’s performance [...] Read more.
The human operator largely relies on the perception of remote environmental conditions to make timely and correct decisions in a prescribed task when the robot is teleoperated in a remote place. However, due to the unknown and dynamic working environments, the manipulator’s performance and efficiency of the human-robot interaction in the tasks may degrade significantly. In this study, a novel method of human-centric interaction, through a physiological interface was presented to capture the information details of the remote operation environments. Simultaneously, in order to relieve workload of the human operator and to improve efficiency of the teleoperation system, an updated regression method was proposed to build up a nonlinear model of demonstration for the prescribed task. Considering that the demonstration data were of various lengths, dynamic time warping algorithm was employed first to synchronize the data over time before proceeding with other steps. The novelty of this method lies in the fact that both the task-specific information and the muscle parameters from the human operator have been taken into account in a single task; therefore, a more natural and safer interaction between the human and the robot could be achieved. The feasibility of the proposed method was demonstrated by experimental results. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Evaluation of Calf Muscle Reflex Control in the ‘Ankle Strategy’ during Upright Standing Push-Recovery
Appl. Sci. 2019, 9(10), 2085; https://doi.org/10.3390/app9102085
Received: 28 February 2019 / Revised: 16 May 2019 / Accepted: 16 May 2019 / Published: 21 May 2019
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Abstract
Revealing human internal control mechanisms during environmental interaction remains paramount and helpful in solving issues related to human-robot interaction. Muscle reflexes, which can directly and rapidly modify the dynamic behavior of joints, are the fundamental control loops of the Central Nervous System. This [...] Read more.
Revealing human internal control mechanisms during environmental interaction remains paramount and helpful in solving issues related to human-robot interaction. Muscle reflexes, which can directly and rapidly modify the dynamic behavior of joints, are the fundamental control loops of the Central Nervous System. This study investigates the calf muscle reflex control in the “ankle strategy” for human push-recovery movement. A time-increasing searching method is proposed to evaluate the feasibility of the reflex model in terms of predicting real muscle activations. Constraints with physiological implications are imposed to find the appropriate reflex gains. The experimental results show that the reflex model fits over 90% of the forepart of muscle activation. With the increasing of time, the Variance Accounted For (VAF) values drop to below 80% and reflex gains lose the physiology meaning. By dividing the muscle activation into two parts, the reflex formula is still workable for the rest part, with different gains and lower VAF values. This result may indicate that reflex control could more likely dominate the forepart of the push-recovery motion and an analogous control mechanism is still feasible for the rest of the motion part, with different gains. The proposed method provides an alternative way to obtain the human internal control mechanism desired for human-robot interaction task. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Hybrid Spiral STC-Hedge Algebras Model in Knowledge Reasonings for Robot Coverage Path Planning and Its Applications
Appl. Sci. 2019, 9(9), 1909; https://doi.org/10.3390/app9091909
Received: 19 February 2019 / Revised: 11 April 2019 / Accepted: 26 April 2019 / Published: 9 May 2019
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Abstract
Robotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path [...] Read more.
Robotics is a highly developed field in industry, and there is a large research effort in terms of humanoid robotics, including the development of multi-functional empathetic robots as human companions. An important function of a robot is to find an optimal coverage path planning, with obstacle avoidance in dynamic environments for cleaning and monitoring robotics. This paper proposes a novel approach to enable robotic path planning. The proposed approach combines robot reasoning with knowledge reasoning techniques, hedge algebra, and the Spiral Spanning Tree Coverage (STC) algorithm, for a cleaning and monitoring robot with optimal decisions. This approach is used to apply knowledge inference and hedge algebra with the Spiral STC algorithm to enable autonomous robot control in the optimal coverage path planning, with minimum obstacle avoidance. The results of experiments show that the proposed approach in the optimal robot path planning avoids tangible and intangible obstacles for the monitoring and cleaning robot. Experimental results are compared with current methods under the same conditions. The proposed model using knowledge reasoning techniques in the optimal coverage path performs better than the conventional algorithms in terms of high robot coverage and low repetition rates. Experiments are done with real robots for cleaning in dynamic environments. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
An Extended Proxy-Based Sliding Mode Control of Pneumatic Muscle Actuators
Appl. Sci. 2019, 9(8), 1571; https://doi.org/10.3390/app9081571
Received: 24 March 2019 / Revised: 10 April 2019 / Accepted: 12 April 2019 / Published: 16 April 2019
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Abstract
To solve the problem of controlling an intrinsically compliant actuator, pneumatic muscle actuator (PMA), this paper presents an extended proxy-based sliding mode control (EPSMC) strategy. It is well known that the chattering phenomenon of conventional sliding mode control (SMC) can be effectively solved [...] Read more.
To solve the problem of controlling an intrinsically compliant actuator, pneumatic muscle actuator (PMA), this paper presents an extended proxy-based sliding mode control (EPSMC) strategy. It is well known that the chattering phenomenon of conventional sliding mode control (SMC) can be effectively solved by introducing a proxy between the physical object and desired position, which results in the so-called proxy-based sliding mode control (PSMC). To facilitate the theoretical analysis of PSMC and obtain a more general form of controller, a new virtual coupling and a SMC are used in our proposed EPSMC. For a class of second-order nonlinear system, the sufficient conditions ensuring the stability and passivity are obtained by using the Lyapunov functional method. Experiments on a real-time PMA control platform validate the effectiveness of the proposed method, and comparison studies also show the superiority of EPSMC over the conventional SMC, PSMC, and PID controllers. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Learning, Generalization, and Obstacle Avoidance with Dynamic Movement Primitives and Dynamic Potential Fields
Appl. Sci. 2019, 9(8), 1535; https://doi.org/10.3390/app9081535
Received: 12 March 2019 / Revised: 10 April 2019 / Accepted: 10 April 2019 / Published: 12 April 2019
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Abstract
In order to offer simple and convenient assistance for the elderly and disabled to take care of themselves, we propose a general learning and generalization approach for a service robot to accomplish specified tasks autonomously in an unstructured home environment. This approach firstly [...] Read more.
In order to offer simple and convenient assistance for the elderly and disabled to take care of themselves, we propose a general learning and generalization approach for a service robot to accomplish specified tasks autonomously in an unstructured home environment. This approach firstly learns the required tasks by learning from demonstration (LfD) and represents the learned tasks with dynamic motion primitives (DMPs), so as to easily generalize them to a new environment only with little modification. Furthermore, we integrate dynamic potential field (DPF) with the above DMPs model to realize the autonomous obstacle avoidance function of a service robot. This approach is validated on the wheelchair mounted robotic arm (WMRA) by performing serial experiments of placing a cup on the table with an obstacle or without obstacle on its motion path. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Quadrupedal Robots Whole-Body Motion Control Based on Centroidal Momentum Dynamics
Appl. Sci. 2019, 9(7), 1335; https://doi.org/10.3390/app9071335
Received: 19 February 2019 / Revised: 16 March 2019 / Accepted: 22 March 2019 / Published: 29 March 2019
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Abstract
In this paper, we demonstrate a method for quadruped dynamic locomotion based on centroidal momentum control. Our method relies on a quadratic program that solves an optimal control problem to track the reference rate of change of centroidal momentum as closely as possible [...] Read more.
In this paper, we demonstrate a method for quadruped dynamic locomotion based on centroidal momentum control. Our method relies on a quadratic program that solves an optimal control problem to track the reference rate of change of centroidal momentum as closely as possible while satisfying the dynamic, input, and contact constraints of the full quadruped robot dynamics. Given the desired footstep positions, the according reference rate of change of the centroidal momentum is formulated as a feedback control task derived from the CoM motions of a simplified model (linear inverted pendulum) based on Capture Point dynamics. The joint accelerations and the Ground Reaction Forces(GRFs) outputted from the quadratic program solver are used to calculate the desired joint torques using an inverse dynamics algorithm. The performance of the proposed method is tested in simulation and on real hardware. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
The Exoskeleton Balance Assistance Control Strategy Based on Single Step Balance Assessment
Appl. Sci. 2019, 9(5), 884; https://doi.org/10.3390/app9050884
Received: 25 January 2019 / Revised: 19 February 2019 / Accepted: 26 February 2019 / Published: 1 March 2019
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Abstract
A novel balance assistance control strategy of a hip exoskeleton robot was proposed in this paper. The organic fusion of the human balance assessment and the exoskeleton balance assistance control strategy are the assurance of balance recovery. However, currently there are few human [...] Read more.
A novel balance assistance control strategy of a hip exoskeleton robot was proposed in this paper. The organic fusion of the human balance assessment and the exoskeleton balance assistance control strategy are the assurance of balance recovery. However, currently there are few human balance assessment methods that are suitable for detecting balance loss during standing and walking, and very little research has focused on exoskeleton balance recovery control. In this paper, a single step balance assessment method was proposed first, and then based on this method an "assist-as-needed" balance assistance control strategy was established. Finally, the exoskeleton balance assistance control experiment was carried out. The experiment results verified the effectiveness of the single balance assessment method and the active balance assistance control strategy. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Robot Navigation Based on Human Trajectory Prediction and Multiple Travel Modes
Appl. Sci. 2018, 8(11), 2205; https://doi.org/10.3390/app8112205
Received: 21 September 2018 / Revised: 24 October 2018 / Accepted: 7 November 2018 / Published: 9 November 2018
Cited by 1 | PDF Full-text (6357 KB) | HTML Full-text | XML Full-text
Abstract
For a mobile robot, navigation skills that are safe, efficient, and socially compliant in crowded, dynamic environments are essential. This is a particularly challenging problem as it requires the robot to accurately predict pedestrians’ movements, analyse developing traffic situations, and plan its own [...] Read more.
For a mobile robot, navigation skills that are safe, efficient, and socially compliant in crowded, dynamic environments are essential. This is a particularly challenging problem as it requires the robot to accurately predict pedestrians’ movements, analyse developing traffic situations, and plan its own path or trajectory accordingly. Previous approaches still exhibit low accuracy for pedestrian trajectory prediction, and they are prone to generate infeasible trajectories under complex crowded conditions. In this paper, we develop an improved socially conscious model to learn and predict a pedestrian’s future trajectory. To generate more efficient and safer trajectories in a changing crowed space, an online path planning algorithm considering pedestrians’ predicted movements and the feasibility of the candidate trajectories is proposed. Then, multiple traffic states are defined to guide the robot finding the optimal navigation strategies under changing traffic situations in a crowded area. We have demonstrated the performance of our approach outperforms state-of-the-art approaches with public datasets, in low-density and simulated medium-density crowded scenarios. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Real-Time Whole-Body Imitation by Humanoid Robots and Task-Oriented Teleoperation Using an Analytical Mapping Method and Quantitative Evaluation
Appl. Sci. 2018, 8(10), 2005; https://doi.org/10.3390/app8102005
Received: 23 August 2018 / Revised: 30 September 2018 / Accepted: 18 October 2018 / Published: 22 October 2018
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Abstract
Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable [...] Read more.
Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed system. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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Open AccessArticle
Towards Online Estimation of Human Joint Muscular Torque with a Lower Limb Exoskeleton Robot
Appl. Sci. 2018, 8(9), 1610; https://doi.org/10.3390/app8091610
Received: 9 August 2018 / Revised: 7 September 2018 / Accepted: 8 September 2018 / Published: 11 September 2018
Cited by 2 | PDF Full-text (2289 KB) | HTML Full-text | XML Full-text
Abstract
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity. Joint muscular torques (JMT) reflect human effort, which can be applied on an exoskeleton robot to realize an active power-assist function. The estimation of human JMT with a wearable [...] Read more.
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity. Joint muscular torques (JMT) reflect human effort, which can be applied on an exoskeleton robot to realize an active power-assist function. The estimation of human JMT with a wearable exoskeleton is challenging. This paper proposed a novel human lower limb JMT estimation method based on the inverse dynamics of the human body. The method has two main parts: the inverse dynamic approach (IDA) and the sensing system. We solve the inverse dynamics of each human leg separately to shorten the serial chain and reduce computational complexity, and divide the JMT into the mass-induced one and the foot-contact-force (FCF)-induced one to avoid switching the dynamic equation due to different contact states of the feet. An exoskeleton embedded sensing system is designed to obtain the user’s motion data and FCF required by the IDA by mapping motion information from the exoskeleton to the human body. Compared with the popular electromyography (EMG) and wearable sensor based solutions, electrodes, sensors, and complex wiring on the human body are eliminated to improve wearing convenience. A comparison experiment shows that this method produces close output to a motion analysis system with different subjects in different motion. Full article
(This article belongs to the Special Issue Human Friendly Robotics)
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