Automation fears: Drivers and solutions

New technologies offer employers the ability to replace tasks done by human labour with those done by machines. There are challenges for both employers and employees, as employers look for strategies for the implementation of automation technologies and employees may have concerns about their employment being threatened by automation technologies. In this research, we analyse data of over 500 Bulgarians to learn about how they perceive the automation of their jobs. The analysis finds that there are segments of the population defined by demographics and attitudes that are more fearful of the automation of their jobs than others. Additionally, we see that attitudes towards the dehumanizing effects of automation, peer-pressure, job automatability, and a person's self-perception of professionalism are the main drivers of the fear of automation. Finally, the paper evaluates respondents' attitudes towards various individual, corporate and social solutions to automation fears.     

Team O2AS at the world robot summit 2018: an approach to robotic kitting and assembly tasks using general purpose grippers and tools

ABSTRACT

In this article, we propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of the Industrial Robotics Category of the World Robot Challenge at the World Robot Summit 2018, obtaining 4th place and the SICE award for lean design and versatile tool use. We show the effectiveness of our approach through experiments performed during the competition.     

EPSRC Principles of Robotics: defending an obsolete human(ism)?

ABSTRACT

The EPSRC Principles of Robotics (2010), whatever noble intentions, failed to create an enduring set of principles for research into and development of robotics and artificial intelligence because those participating in the workshop did not begin with an adequate understanding of what it means to be “human”. Labouring under the false, outdated assumptions of humanism, the human beings that the Principles are meant to serve have never existed in such an overly-simplistic form, or are soon to be made extinct by the transformative power of new technologies, and new ways of imagining human social relations in response to technological innovation. At the heart of any principles for robotics must be a new, more flexible conception of what it means to be human, and a recognition that human beings are, and always will be, plural and contingent.     

Ethics of healthcare robotics: Towards responsible research and innovation

How can we best identify, understand, and deal with ethical and societal issues raised by healthcare robotics? This paper argues that next to ethical analysis, classic technology assessment, and philosophical speculation we need forms of reflection, dialogue, and experiment that come, quite literally, much closer to innovation practices and contexts of use. The authors discuss a number of ways how to achieve that. Informed by their experience with “embedded” ethics in technical projects and with various tools and methods of responsible research and innovation, the paper identifies “internal” and “external” forms of dialogical research and innovation, reflections on the possibilities and limitations of these forms of ethical–technological innovation, and explores a number of ways how they can be supported by policy at national and supranational level.     

Will robots know us better than we know ourselves?

This paper aims to highlight some conceptual aspects on the impact of robotics on our concept of privacy. In those areas where robotics applications will invade the privacy of individuals as computers or mobile phones do today, the current idea of privacy will no longer suffice to ensure the right level of people’s protection. If we think to answer or stop the forthcoming controversies only relying on self-regulation of private parties, we will escape the real challenge: the next generation of robots does not affect solely persons and their individual rights, but the entire structure of society. This article assumes the robotics–privacy relationship as a clear illustration of how the technology–society nexus should be regulated in the future. We need approaches that are contextual–normativeand that should be politically addressed to the creation of a critical culture of technology.     

Software and hardware architecture of advanced mobile robots for manufacturing

Modern manufacturing requires flexible and autonomous systems for materials handling and transportation. For such applications, a succession of implemented mobile robots has been developed over the past seven years. In this paper, the questions of software and hardware architecture are discussed in light of experience gained so far. Also discussed are mobile robot projects that seem realistic over the next five to ten years.     

A fractional approach for the motion planning of redundant and hyper-redundant manipulators

The trajectory planning of redundant robots through the pseudoinverse control leads to undesirable drift in the joint space. This paper presents a new technique to solve the inverse kinematics problem of redundant manipulators, which uses a fractional differential of order α to control the joint positions. Two performance measures are defined to examine the strength and weakness of the proposed method. The positional error index measures the precision of the manipulator's end-effector at the target position. The repeatability performance index is adopted to evaluate if the joint positions are repetitive when the manipulator execute repetitive trajectories in the operational workspace. Redundant and hyper-redundant planar manipulators reveal that it is possible to choose in a large range of possible values of α in order to get repetitive trajectories in the joint space.     

Shaping: The Link Between Rats and Robots

The term shaping applies to a family of procedures which were originally developed in animal learning as methods of producing new and sometimes elaborate forms of behavior. The success of operant shaping methods in animal and abnormal psychology has attracted the attention of some roboticists who view these procedures as a means of generating adaptive behavior in both simulated and real robots. This paper outlines the two principal forms of shaping and looks at some of the associative and motivational influences which determine the course and outcome of shaping methods in animals. A number of recent robotic models which incorporate operant shaping concepts are then reviewed in terms of their eff ectiveness; the conclusion from this analysis is that, while some progress has been made, none of these models represent a satisfactory application of animal shaping procedures. It is clear that an effective implementation of shaping methods in behaviorbased robotics requires both a better understanding of the nature and course of shaping in real animals and the development, by roboticists and others, of more sophisticated models which can exploit this improved understanding.     

On the learning control of a robot manipulator

This paper derives a learning control law to achieve trajectory following for a robot manipulator. The controller consists of two parts, a computed torque servo for the rigid body terms that can be modelled and a learning law for the unmodelled dynamics. An advantage of this method is that bounds can be assigned to the position and velocity tracking errors.     

Optimal robot task scheduling based on genetic algorithms

Industrial robots should perform complex tasks in the minimum possible cycle time in order to obtain high productivity. The problem of determining the optimum route of a manipulator's end effector visiting a number of task points is similar but not identical to the well-known travelling salesman problem (TSP). Adapting TSP to Robotics, the measure to be optimized is the time instead of the distance. In addition, the travel time between any two points is significantly affected by the choice of the manipulator's configuration. Therefore, the multiple solutions of the inverse kinematics problem should be taken into consideration.In this paper, a method is introduced to determine the optimum sequence of task points visited by the tip of the end effector of an articulated robot and it can be applied to any non-redundant manipulator. This method is based on genetic algorithms and an innovative encoding is introduced to take into account the multiple solutions of the inverse kinematic problem. The results show that the method can determine the optimum sequence of a considerable number of task points for robots up to six-degrees of freedom.