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Unlike the historical robots, the contemporary and futuristic ‘working’ robots within organisations are capable of taking decisions without human intervention. This chapter reviews the technical evolution of robots across history with the necessary evolution of operational procedures regarding laws and ethical standards. The objective of this review is to have a futuristic holistic insight into the new generation of robots that are invading our working environment within organisations. Out of the very wide perspective of robotics research field, this chapter only discusses the ‘working’ robots (excluding domestic, social, and warfare robots) in organisations along with its ethical and legal associated issues. To achieve this objective, the recent ‘working robot’ definition and associated expected ethics and laws, termed in this chapter as ‘Ten Commandments’ would be necessary for the utilisation of robotics before releasing ‘intelligent’ robots in the workplace environment. The proposed ‘Ten Commandments’ can be utilised by robot manufacturer to embed ‘machine testimony’ to their products. Providing that such ‘robot ethics’ built as part of the algorithmic structure of robots, a useful innovation like robot–manager is also identified in the organisational environment which can have multiple benefits as discussed in this chapter.

This paper aims to address a new iterative tuning method of PID control for robot manipulators.

This tuning method uses several properties of the robot control, such as any PD control can stabilize a robot in regulation case, the closed-loop system of PID control can be approximated by a linear system, the control torque to the robot manipulator is linearly independent of the robot dynamic.

Compared with the other PID tuning methods, this novel method is simple, systematic, and stable. The transient properties of this PID control are better than the other normal PID controllers.

In this paper, a new systematic tuning method for PID control is proposed. The paper applies this method on an upper limb exoskeleton, and real experiment results give validation of our PID tuning method.

The aim of this paper is to propose a robust robot fuzzy logic proportional-derivative (PD) controller for trajectory tracking of autonomous nonholonomic differential drive wheeled mobile robot (WMR) of the type Quanser Qbot.

Fuzzy robot control approach is used for developing a robust fuzzy PD controller for trajectory tracking of a nonholonomic differential drive WMR. The linear/angular velocity of the differential drive mobile robot are formulated such that the tracking errors between the robot’s trajectory and the reference path converge asymptotically to zero. Here, a new controller zero-order Takagy–Sugeno trajectory tracking (ZTS-TT) controller is deduced for robot’s speed regulation based on the fuzzy PD controller. The WMR used for the experimental implementation is Quanser Qbot which has two differential drive wheels; therefore, the right/left wheel velocity of the differential wheels of the robot are worked out using inverse kinematics model. The controller is implemented using MATLAB Simulink with QUARC framework, downloaded and compiled into executable (.exe) on the robot based on the WIFI TCP/IP connection.

Compared to other fuzzy proportional-integral-derivative (PID) controllers, the proposed fuzzy PD controller was found to be robust, stable and consuming less resources on the robot. The comparative results of the proposed ZTS-TT controller and the conventional PD controller demonstrated clearly that the proposed ZTS-TT controller provides better tracking performances, flexibility, robustness and stability for the WMR.

The proposed fuzzy PD controller can be improved using hybrid techniques. The proposed approach can be developed for obstacle detection and collision avoidance in combination with trajectory tracking for use in environments with obstacles.

A robust fuzzy logic PD is developed and its performances are compared to the existing fuzzy PID controller. A ZTS-TT controller is deduced for trajectory tracking of an autonomous nonholonomic differential drive mobile robot (i.e. Quanser Qbot).

The purpose of this paper is to identify the factors influencing the citizens to use robots that would improve the quality of life of the citizens.

With the help of different adoption theories and models and with the support of background studies, some hypotheses have been formulated and a conceptual model has been developed with the consideration of the impact of artificial intelligence regulation (IAR) that controls the use of robots as a moderator. The model has been validated and the hypotheses have been tested by statistical analysis with the help of survey works involving consideration of feedbacks from 503 usable respondents.

The study reveals that the use of robots by the citizens would appreciably increase if government imposes strict artificial intelligence (AI) regulatory control concerning the use of robots, and in that case, it appears that the use of robots would improve the quality of life of the citizens.

The duly validated model would help the authority to appropriately nurse and nurture the factors such as ethical dilemma, perceived risks and control beliefs for enhancing the intention of the citizens to use robots for many purposes including domestic usage in the context of appropriate restrictions imposed through AI regulation. Such use of robots would eventually improve the quality of life.

There are a few studies covering analysis of IAR as a moderator on the linkages of the predictors with the intention of the citizens to use robots. In this context, this study is claimed to have offered a novel contribution.

The purpose of this paper is to transfer the impedance regulation of manual belt grinding to robot belt grinding control.

This paper presents a novel methodology for transmitting human impedance regulation skills to robot control in robot belt grinding. First, according to the human grinding experimental data, the skilled worker’s arm impedance regulation is calculated. Next, the human skills are encapsulated as the statistical learning model where the kernel parameters are learned from the demonstration data by Gaussian process regression (GPR) algorithms. The desired profiles of robot are generated by the task planner based on the learned skill knowledge model. Lastly, the learned skill knowledge model is integrated with an adaptive hybrid position-force controller over the trajectory and force of end-effector in robot belt grinding task.

Manual grinding skills are represented and transferred to robot belt grinding for higher grinding quality of the workpiece.

The impedance of the manual grinding is estimated by k-means++ algorithm at different grinding phases. Manual grinding skills (e.g. trajectory, impedance regulation) are represented and modeled by GMM and GPR algorithms. The desired trajectory, force and impedance of robot are generated by the planner based on the learned skills knowledge model. An adaptive hybrid position-force controller is designed based on learned skill knowledge model. This paper proposes a torque-tracking controller to suppress the vibration in robot belt grinding process.

Teaching by demonstration (TbD) is a promising way for robot learning skills in human and robot collaborative hybrid manufacturing lines. Traditionally, TbD systems have only concentrated on how to enable robots to learn movement skills from humans. This paper aims to develop an extended TbD system which can also enable learning stiffness regulation strategies from humans.

Here, the authors propose an extended dynamical motor primitives (DMP) framework to achieve this goal. In addition to the advantages of the traditional ones, the authors’ framework can enable robots to simultaneously learn stiffness and the movement from human demonstrations. Additionally, Gaussian mixture model (GMM) is used to capture the features of movement and of stiffness from multiple demonstrations of the same skill. Human limb surface electromyography (sEMG) signals are estimated to obtain the reference stiffness profiles.

The authors have experimentally demonstrated the effectiveness of the proposed framework. It shows that the authors approach could allow the robot to execute tasks in a variable impedance control mode with the learned movement trajectories and stiffness profiles.

In robot skill acquisition, DMP is widely used to encode robotic behaviors. So far, however, these DMP modes do not provide the ability to properly represent and generalize stiffness profiles. The authors argue that both movement trajectories and stiffness profiles should be considered equally in robot skill learning. The authors’ approach has great potential of applications in the future hybrid manufacturing lines.

This paper aims to present the optimal design procedure of a symmetrical 2-DOF parallel planar robot with flexible joints by considering several performance criteria based on the workspace size, dynamic dexterity and energy of the control.

Consequently, the optimal design consists in determining the dimensional parameters to maximize the size of the workspace, maximize the dynamic dexterity and minimize the energy of the control action. The design criteria are derived from the kinematics, dynamics, elastodynamics and the position control law of the robot. The analysis of the design criteria is performed by means of the design space and atlases.

Finally, the multi-objective design optimization derived from the optimal design procedure is solved by using multi-objective genetic algorithms, and the results are analyzed to assess the validity of the proposed approach.

An alternative approach to the design of a planar parallel robot with flexible joints that permits determining the structural parameters by considering kinematic, dynamic and control operational performance.

The construction industry is the major sector in China but it has been exposed to a series of problems including low productivity and workforce shortage. However, construction robots as an effective and sustainable approach to overcome the difficulties in construction industry have not been widely adopted. Few studies attempted to investigate on the adoption of construction robots in China. In order to fill this gap, this study aim to address the barriers to the adoption of construction robots in China.

Through literature review, semi-structured interview 24 factors hindering the adoption of construction robots are summarized. Next, a total of valid 150 questionnaires delivered to the 7 stakeholders were collected. Ranking analysis was used to identify 21 critical factors was determined by the mean score analysis and factor analysis extracted 21 critical factors into 5 clusters.

Results indicate that the “technological performance and management” cluster is the most dominant of the 5 clusters. The most important barrier is “Limited research and design input”, followed by “High purchase cost” and “Unstructured construction environment”. Construction robots are still under R&D have had limited field applications in the production and construction process.

The research findings provide a useful reference for different stakeholders to identify the critical factors appropriate strategies to promote the adoption of construction robots. Furthermore, this study provides recommendations to promote adoption of construction robots.

Purpose: The research investigates the presence of technology ideologies in consumer discourse on tourism and hospitality robots.

Design/methodology/approach: Using a netnographic approach, the research involved immersion in online discourses and collection of consumer posts from a variety of social media platforms. Data was subjected to a thematic analysis informed by the technology ideology framework described in the literature review.

Findings: Online consumer narratives about tourism and hospitality robots are dynamic and varied and reveal a multitude of technology ideology-related positions. The research confirms the applicability of the technology ideology framework to online discourses on service robots and finds that anthropomorphism triggers additional concerns.

Research implications: The findings suggest that future research on the acceptance and use of service robots should go beyond psychological concepts.

Practical implications: Without uncovering and understanding technology sensemaking processes with respect to service robots, the introduction of service robots in hospitality and tourism might trigger consumer resistance or lead to inferior service experiences.

Social implications: The research suggests that sensemaking of technology, specifically service robots, is complex and colored by pertinent ideologies. Policies and regulations regarding service robot adoption and implementation should consider these various positions.

Originality/value: The paper introduces technology sensemaking and technology ideology as important theoretical frameworks to understand consumer perceptions, attitudes, uses and relationships in regard to service robots in hospitality and tourism contexts.

The purpose of this paper is to present a control system for a heavy duty industrial robot, including both the control structure and algorithm, which was designed and tested.

An industrial PC with TwinCAT real‐time system is chosen as the motion control unit; EtherCAT is used for command transmission. The whole system has a decoupled and centralized control structure. A novel optimal motion generation algorithm based on modified cubic spline interpolation is illustrated. The execution time and work were chosen as the objective function. The constraints are the limits of torque, velocity and jerk. The motion commands were smooth enough throughout the execution period. By using the Lagangue equation and assumed modes methods, a dynamic model of heavy duty industrial robots is built considering the elastic of both joints and links. After that a compound control algorithm based on singular perturbation theory was designed for the servo control loop.

The final experimental results showed that the control commands and algorithms could easily be calculated and transmitted in one sample unit. Both the motion generation and servo control algorithm greatly improved the control performance of the robot.

All parts of the control algorithm can be computed on‐line except the optimal motion generation part. The motion generation part is time consuming (about 2.5 seconds), which can only be performed off‐line. Hence future work will focus on improving the efficiency of this algorithm; therefore it could be performed online, increasing the robot's overall robustness and adaptability.

Aiming at the internal and external causes that limit the dynamic performance of heavy duty industrial robots, this paper proposes a realizable scheme of control system and includes both the control structure and algorithms. A novel optimal motion generation algorithm is presented.