Multi-robot team formation control in the GUARDIANS project

Purpose The GUARDIANS multi-robot team is to be deployed in a large warehouse in smoke. The team is to assist firefighters search the warehouse in the event or danger of a fire. The large dimensions of the environment together with development of smoke which drastically reduces visibility, represent major challenges for search and rescue operations. The GUARDIANS robots guide and accompany the firefighters on site whilst indicating possible obstacles and the locations of danger and maintaining communications links. Design/methodology/approach In order to fulfill the aforementioned tasks the robots need to exhibit certain behaviours. Among the basic behaviours are capabilities to stay together as a group, that is, generate a formation and navigate while keeping this formation. The control model used to generate these behaviours is based on the so-called social potential field framework, which we adapt to the specific tasks required for the GUARDIANS scenario. All tasks can be achieved without central control, and some of the behaviours can be performed without explicit communication between the robots. Findings The GUARDIANS environment requires flexible formations of the robot team: the formation has to adapt itself to the circumstances. Thus the application has forced us to redefine the concept of a formation. Using the graph-theoretic terminology, we can say that a formation may be stretched out as a path or be compact as a star or wheel. We have implemented the developed behaviours in simulation environments as well as on real ERA-MOBI robots commonly referred to as Erratics. We discuss advantages and shortcomings of our model, based on the simulations as well as on the implementation with a team of Erratics.</p

A phenomenological study of the impact of knowledge intensity and environmental velocity on in source or hosted contact centres.

Contact centres exist in order to focus the final step of the intra organisational value chain which then delivers optimalcustomer satisfaction. In this paper we analyse a centre with a view to investigating the impact of outsourcing or the inhouselocus of provision. Such centres exhibit agency/principal characteristics, bringing knowledge management into sharp focus, aspects of information intensity which impact on the organisational dynamics, and the learning of the employees. A phenomenological approach to determine the essence of the activities was deployed rather than a methodological initiative based post positivistic strategic analysis. The characteristics of contact centres investigated coalesce into two distinct categories; a framework to depict this is presented

A Competency-based Approach toward Curricular Guidelines for Information Technology Education

The Association for Computing Machinery and the IEEE Computer Society have launched a new report titled, Curriculum Guidelines for Baccalaureate Degree Programs in Information Technology (IT2017). This paper discusses significant aspects of the IT2017 report and focuses on competency-driven learning rather than delivery of knowledge in information technology (IT) programs. It also highlights an IT curricular framework that meets the growing demands of a changing technological world in the next decade. Specifically, the paper outlines ways by which baccalaureate IT programs might implement the IT curricular framework and prepare students with knowledge, skills, and dispositions to equip graduates with competencies that matter in the workplace. The paper suggests that a focus on competencies allows academic departments to forge collaborations with employers and engage students in professional practice experiences. It also shows how professionals and educators might use the report in reviewing, updating, and creating baccalaureate IT degree programs worldwide

An analysis of the requirements traceability problem

In this paper1, we investigate and discuss the underlying nature of the requirements traceability problem. Our work is based on empirical studies, involving over 100 practitioners, and an evaluation of current support. We introduce the distinction between pre-requirements specification (pre-RS) traceability and post-requirements specification (post-RS) traceability, to demonstrate why an all-encompassing solution to the problem is unlikely, and to provide a framework through which to understand its multifaceted nature. We report how the majority of the problems attributed to poor requirements traceability are due to inadequate pre-RS traceability and show the fundamental need for improvements here. In the remainder of the paper, we present an analysis of the main barriers confronting such improvements in practice, identify relevant areas in which advances have been (or can be) made, and make recommendations for research

Machine Understanding of Human Behavior

A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning

Most successes in robotic manipulation have been restricted to single-arm gripper robots, whose low dexterity limits the range of solvable tasks to pick-and-place, inser-tion, and object rearrangement. More complex tasks such as assembly require dual and multi-arm platforms, but entail a suite of unique challenges such as bi-arm coordination and collision avoidance, robust grasping, and long-horizon planning. In this work we investigate the feasibility of training deep reinforcement learning (RL) policies in simulation and transferring them to the real world (Sim2Real) as a generic methodology for obtaining performant controllers for real-world bi-manual robotic manipulation tasks. As a testbed for bi-manual manipulation, we develop the U-Shape Magnetic BlockAssembly Task, wherein two robots with parallel grippers must connect 3 magnetic blocks to form a U-shape. Without manually-designed controller nor human demonstrations, we demonstrate that with careful Sim2Real considerations, our policies trained with RL in simulation enable two xArm6 robots to solve the U-shape assembly task with a success rate of above90% in simulation, and 50% on real hardware without any additional real-world fine-tuning. Through careful ablations,we highlight how each component of the system is critical for such simple and successful policy learning and transfer,including task specification, learning algorithm, direct joint-space control, behavior constraints, perception and actuation noises, action delays and action interpolation. Our results present a significant step forward for bi-arm capability on real hardware, and we hope our system can inspire future research on deep RL and Sim2Real transfer of bi-manualpolicies, drastically scaling up the capability of real-world robot manipulators.Comment: Our accompanying project webpage can be found at: https://sites.google.com/view/u-shape-block-assembly. arXiv admin note: substantial text overlap with arXiv:2203.0827

Evaluating weaknesses of "perceptual-cognitive training" and "brain training" methods in sport: An ecological dynamics critique

The recent upsurge in "brain training and perceptual-cognitive training," proposing to improve isolated processes, such as brain function, visual perception, and decision-making, has created significant interest in elite sports practitioners, seeking to create an "edge" for athletes. The claims of these related "performance-enhancing industries" can be considered together as part of a process training approach proposing enhanced cognitive and perceptual skills and brain capacity to support performance in everyday life activities, including sport. For example, the "process training industry" promotes the idea that playing games not only makes you a better player but also makes you smarter, more alert, and a faster learner. In this position paper, we critically evaluate the effectiveness of both types of process training programmes in generalizing transfer to sport performance. These issues are addressed in three stages. First, we evaluate empirical evidence in support of perceptual-cognitive process training and its application to enhancing sport performance. Second, we critically review putative modularized mechanisms underpinning this kind of training, addressing limitations and subsequent problems. Specifically, we consider merits of this highly specific form of training, which focuses on training of isolated processes such as cognitive processes (attention, memory, thinking) and visual perception processes, separately from performance behaviors and actions. We conclude that these approaches may, at best, provide some "general transfer" of underlying processes to specific sport environments, but lack "specificity of transfer" to contextualize actual performance behaviors. A major weakness of process training methods is their focus on enhancing the performance in body "modules" (e.g., eye, brain, memory, anticipatory sub-systems). What is lacking is evidence on how these isolated components are modified and subsequently interact with other process "modules," which are considered to underlie sport performance. Finally, we propose how an ecological dynamics approach, aligned with an embodied framework of cognition undermines the rationale that modularized processes can enhance performance in competitive sport. An ecological dynamics perspective proposes that the body is a complex adaptive system, interacting with performance environments in a functionally integrated manner, emphasizing that the inter-relation between motor processes, cognitive and perceptual functions, and the constraints of a sport task is best understood at the performer-environment scale of analysis