Simulation of a high recirculation airlift reactor for steady-state operation

Gegov²

2013

Assembly Automation

This paper reviews some of those tools. Applications of these tools in Assembly Automation have become more widespread due to the power and affordability of present-day computers. Research limitations/implications (limit 100 words): Many new Assembly Automation applications may emerge and greater use may be made of hybrid tools that combine the strengths of two or more of the tools reviewed in the paper. The tools and methods reviewed in this paper have minimal computation complexity and can be implemented on small assembly lines, single robots or systems with low-capability microcontrollers. Practical implications (limit 100 words): It may take another decade for engineers to recognize the benefits given the current lack of familiarity and the technical barriers associated with using these tools and it may take a long time for direct digital manufacturing to be considered commonplace… but it is expanding. The appropriate deployment of the new AI tools will contribute to the creation of more competitive Assembly Automation systems. Social Implications (limit 100 words): Other technological developments in AI that will impact on Assembly Automation include data mining, multi-agent systems and distributed self-organising systems. Originality/value (limit 100 words): The novel approaches proposed use Ambient Intelligence and the mixing of different AI tools in an effort to use the best of each technology. The concepts are generically applicable across all industrial assembly processes and this research is intended to prove that the concepts work in manufacturing.

Section: Some Artificial Intelligence Applications At the University mentioning

confidence: 99%

AI tools for use in assembly automation and some examples of recent applications

Gegov²

2013

Assembly Automation

“…That way distance feedback could be provided through the joystick. These will be investigated with automatic programming [61][62][63][64] and Artificial…”

Section: Future Workmentioning

confidence: 99%

Comparing ability to complete simple tele‐operated rescue or maintenance mobile‐robot tasks with and without a sensor system

2010

Sensor Review

The effect on completion of mobile-robot tasks is investigated depending on how a human tele-operator interacts with a sensor system and a mobile-robot. Design/methodology/approach: Interaction is investigated using two mobile-robot systems, three different ways of interacting with the robots and several different environments of increasing complexity. In each case, the operation is investigated with and without sensor systems to assist an operator to move a robot through narrower and narrower gaps and in completing progressively more complicated driving tasks. Tele-operators used a joystick and either watched the robot while operating it, or sat at a computer and viewed scenes remotely on a screen. Cameras were either mounted on the robot to view the space ahead of the robot or mounted remotely so that they viewed both the environment and robot. Every test was compared with sensor systems engaged and with them disconnected. Findings: A main conclusion is that human tele-operators perform better without the assistance of sensor systems in simple environments and in those cases it may be better to switch off the sensor systems or reduce their effect. In addition, tele-operators sometimes performed better with a camera mounted on the robot compared with pre-mounted cameras observing the environment (but that depended on tasks being performed). Research limitations/implications: Tele-operators completed tests both with and without sensors. One robot system used an Umbilical Cable and one used a radio link. Practical implications: The paper quantifies the difference between tele-operation control and sensor assisted control when a robot passes through narrow passages. This could be useful information when system designers decide if a system should be tel-operated, automatic or sensorassisted. The paper suggests that in simple environments then the amount of sensor support should be small but in more complicated environments then more sensor support needs to be provided. Originality/value: The paper investigates the effect of completing mobile-robot tasks depending on whether a human tele-operator uses a sensor system or not and how they interact with the sensor system and the mobile-robot. The paper presents the results from investigations using two mobilerobot systems, three different ways of interacting with the robots and several different environments of increasing complexity. The change in the ability of a human operator to complete progressively more complicated driving tasks with and without a sensor system is presented and the human teleoperators performed better without the assistance of sensor systems in simple environments.

“…The current issue and full text archive of this journal is available at www.emeraldinsight.com/0144-5154.htm Motion planning for manipulators with many degrees of freedom is a complex task (Sanders, 2008c), sometimes requiring AI (Bergasa-Suso et al, 2005;Chester et al, 2006Chester et al, , 2007Hudson et al, 1996Hudson et al, , 1997Sanders, 2009d;Stott et al, 1997). Research in this area has been mostly restricted to static environments or virtual environments (Aguinaga et al, 2007;Sanders, 2000b, Tewkesbury andSanders, 1999a, b) or offline (Solea and Nunes, 2007).…”

Section: Introductionmentioning

confidence: 99%

Simple rules to modify pre‐planned paths and improve gross robot motions associated with pick & place assembly tasks

Tewkesbury²,

Graham-Jones³

2011

Assembly Automation

PurposeThis paper aims to describe real time improvements to the performance and trajectories of robots for which paths had already been planned by some means, automatic or otherwise. The techniques are applied to industrial robots during the gross motions associated with pick and place tasks. Simple rules for path improvement are described.Design/methodology/approachThe dynamics of the manipulator in closed form Lagrange equations are used to represent the dynamics by a set of second‐order coupled non‐linear differential equations. The form of these equations is exploited in an attempt to establish some simple rules. Sub‐optimal paths are improved by considering simple rules developed from the model of the machinery dynamics. By considering the physical limitations of the manipulator, performance was improved by refining pre‐calculated paths. Experiments were performed with a prototype robot and an old Puma 560 robot in a laboratory environment. Once the method had been tested successfully then experiments were conducted with a Kuka KR125 Robot at Ford Motor Company. The measured quantities for all the robots were drive currents to the motors (which represented the torques) and the joint angular positions.FindingsThe method of path refinement presented in this paper uses a simplified model of the robot dynamics to successfully improve the gross motions associated with a pick and place task. The advantage of using the input‐output form described was that intermediate non‐linearities (such as gear friction) and the motor characteristics were directly incorporated into the model.Research limitations/implicationsEven though many of the theoretical problems in manipulator dynamics have been solved, the question of how to best apply the theories to industrial manipulators is still being debated. In the work presented in this paper, information on system dynamics is used to produce simple rules for “path improvement”.Practical implicationsMost fast algorithms are for mobile robots and algorithms are scarcer for manipulators with revolute joints (the most popular type of industrial robot). This work presents real time methods that allow the robot to continue working while new global paths are automatically planned and improved as necessary.Originality/valueMotion planning for manipulators with many degrees of freedom is a complex task and research in this area has been mostly restricted to static environments, offline simulation or virtual environments. This research is applied in real time to industrial robots with revolute joints.