Human management of a robotic swarm

This paper proposes a management algorithm that allows a human operator to organize a robotic swarm via a robot leader. When the operator requests a robot to become a leader, nearby robots suspend their activities. The operator can then request a count of the robots, and assign them into subgroups, one for each task. Once the operator releases the leader, the robots perform the tasks they were assigned to. We report a series of experiments conducted with up to 30 e-puck mobile robots. On average, the counting and allocation algorithm correctly assigns 95 % of the robots in the swarm. The time to count the number of robots increases, on average, linearly with the number of robots, provided they are arranged in random formation

Using Google Glass in human-robot swarm interaction

We study how a human operator can guide a swarm of robots when transporting a large object through an environment with obstacles. The operator controls a leader robot that influences the other robots of the swarm. Follower robots push the object only if they have no line of sight of the leader. The leader represents a way point that the object should reach. By changing its position over time, the operator effectively guides the transporting robots towards the final destination. The operator uses the Google Glass device to interact with the swarm. Communication can be achieved via either touch or voice commands and the support of a graphical user interface. Experimental results with 20 physical e-puck robots show that the human–robot interaction allows the swarm to transport the object through a complex environment

Development of a vision system for TIG welding - a work-in-progress study

The development of a Vision System for TIG Welding has the potential to help realize a real time process monitoring system for joining tasks which require automated welding. A key application of this technique is in the Nuclear Industry; where industrial components require several passes (layers of welding) to achieve robust joints. Through monitoring a welding process such as this in real time, material and time waste could be drastically reduced as faults could be instantly identified. A TIG welding arc is a very intense source of both light and heat, making the creation of a vision system for it challenging. Higher currents result in; brighter TIG welding arcs, higher energy input and deeper and wider weld pools. Nuclear industry applications require deep penetration welding but bright TIG welding arcs can overwhelm the intensity of an auxiliary illumination laser reducing the image clarity of an observing camera system. Thus, a balance between a wide weld bead with clear features applicable to deep penetration but without a brightness level which overwhelms that of the laser must be found. This paper is a Work-in-Progress study of a vision system for TIG welding using an automated TIG welding system and a camera with a laser illumination system. Welding was performed using a Miller Dynasty 350 at 100A with a 3B class laser used to illuminate the weld pool

Evaluating the Radiation Tolerance of a Robotic Finger

In 2024, The Large Hadron Collider (LHC) at CERN will be upgraded to increase its luminosity by a factor of 10 (HL-LHC). The ATLAS inner detector (ITk) will be upgraded at the same time. It has suffered the most radiation damage, as it is the section closest to the beamline, and the particle collisions. Due to the risk of excessive radiation doses, human intervention to decommission the inner detector will be restricted. Robotic systems are being developed to carry out the decommissioning and limit radiation exposure to personnel. In this paper, we present a study of the radiation tolerance of a robotic finger assessed in the Birmingham Cyclotron facility. The finger was part of the Shadow Grasper from Shadow Robot Company, which uses a set of Maxon DC motors

Advantages of virtual reality in the teaching and training of radiation protection during interventions in harsh environments

Human interventions in radioactive environments have high stakes. They are often time-sensitive and radiation exposure must be minimised for the safety of personnel. Existing sites were not developed with remote decommissioning in mind, therefore human intervention remains the preferred approach for dexterous manual labour over robotic systems.For ageing sites, knowledge transfer after retirement is an increasingly relevant problem for maintenance and decommissioning tasks, where new workers lack the in-depth “on the ground” experience of the installation.Virtual Reality provides workers the agency to explore an accurate representation of the area, enabling them to gain experience without undue radiation exposure.This paper explores and discusses the teaching and training applications of a Virtual Reality environment with integrated radiation dose maps, and looks at where the system may be developed further

Robotic additive manufacturing system featuring wire deposition by electric arc for high-value manufacturing

Increasing demand from the high-value manufacturing industries of quality, productivity, efficiency and security aligns with the ambition and driving need for novel automated robotic systems. This paper describes the motivation, design and implementation phases of the SERFOW project (Smart Enabling Robotics driving Free Form Welding). SERFOW is an automated additive manufacturing arc and wire tungsten inert gas (TIG) welding prototype to support industrial manufacturing requirements of the nuclear, aerospace and automotive industry sectors. Key innovations are found in the integration of a 3D vision system with a robotic manipulator to perform automatic free-form fusion welding for the multiple layer additive material build-up required to expand Additive Manufacturing (AM) with minimum human intervention. Welding trials were performed on samples made of Super Duplex stainless steel alloy. Metallographic observations were performed to analyze the porosity distribution and penetration on the material after welding. Also, temperature, feritescope and tensile measurements were performed. The results showed that the welding and AM process performed with the SERFOW cell are within an acceptable quality tolerance range according to the ISO 5817 and the ASME A789 welding standards

Integrating motion capture in a virtual reality intervention planning platform to study radiation protection measures for the ATLAS inner detector decommissioning

An intervention planning and evaluation platform has been developed to enable dose estimation and personnel training for the ATLAS inner detector decommissioning. The present paper describes the integration of motion capture into the system, including the dose estimation results for the recorded decommissioning steps

A feasibility study comparing two commercial TIG welding machines for deep penetration

Developing deep penetration TIG welding to produce welds of equal quality to the industrial standard practise of laser-based welding techniques has the potential to lower production complexity and cost. The detrimental effects of the necessary higher currents required to increase penetration depth in conventional TIG welding have been shown to be circumvented through K-TIG and A-TIG techniques. However, prior experimental work on weld pool dynamics in conventional TIG welding in higher current regions has been sparse as TIG welding enhanced through novel techniques provides the best quality welds. This paper is an early feasibility study for deep penetration welding techniques motivated by observations made during research done at The University of Sheffield where novel activity in the weld pool was identified during TIG welding with a VBC IE500DHC at between 300 and 1 000 A. This current range is labelled the ‘Red Region’. Understanding the weld pool dynamics in the ‘Red Region’ allows the potential exploration of novel techniques for deep penetration TIG welding. Addressing this, the paper compares the quality of welds produced between 100 A and 200 A on 316 Stainless Steel by two industrially leading welding machines; the Miller Dynasty 350 and the VBCie 500DHC

Evaluating the Radiation Tolerance of a Robotic Finger

In 2024, The Large Hadron Collider (LHC) at CERN will be upgraded to increase its luminosity by a factor of 10 (HL-LHC). The ATLAS inner detector (ITk) will be upgraded at the same time. It has suffered the most radiation damage, as it is the section closest to the beamline, and the particle collisions. Due to the risk of excessive radiation doses, human intervention to decommission the inner detector will be restricted. Robotic systems are being developed to carry out the decommissioning and limit radiation exposure to personnel. In this paper, we present a study of the radiation tolerance of a robotic finger assessed in the Birmingham Cyclotron facility. The finger was part of the Shadow Grasper from Shadow Robot Company, which uses a set of Maxon DC motors