What is it about?
This paper is inspired and resulted from a novel PhD project (EPSRC funded) by David Galvao Wall and supervised by John Economou from Cranfield University. Vehicles normally avoid obstacles and are normally single frame systems. However robotic arms have joints and can change their physical geometry similar to a "hand" for a example. Also the robotic arm in this application needs to move in confined spaces without any part of the arm touching any of the obstacles. While at the same time we need to move near these obstacles safely. Algorithms normally take long to calculate how to achieve this. This work discusses how this can be achieved more efficiently.
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Why is it important?
Robotic arm systems that can safely move around dangerous in some cases obstacles is of great importance. Humans can remotely observe the process without having to be near these dangerous situations. This results in a much more safe system, which allows observation for example of suspicious packages within confined spaces.
Perspectives
This research paper is inspiring and addresses some of the realities of algorithms when these are needed to run in real-time. For example, when suspicious packages are found and are required to be explored further there may be time limits as well physical constraints. Hence complex algorithms could produce good solutions however if these take too long to calculate it makes them unrealistic to use in the field. Hence this paper changes this, by taking into account that "real-time algorithm computation" is important especially when "exploration time" is of critical importance. The PhD student has produced with great enthusiasm and research ethos important results which are presented and discussed in the paper in much more detail.
John Economou
Cranfield University
Read the Original
This page is a summary of: Mobile robot arm trajectory generation for operation in confined environments, Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering, December 2014, SAGE Publications,
DOI: 10.1177/0959651814559760.
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