Robots link Northampton, Babylon and Baghdad

A paper has recently being published on a collaboration between University of Northampton; University of Babylon; and University of Technology, Baghdad on path-finding using multiple robots in a dynamic environment.

Full paper is available at: http://research.ijcaonline.org/volume82/number7/pxc3892251.pdf

Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS

Safaa H Shwail, Alia Karim and Scott Turner.
International Journal of Computer Applications

Abstract

In this paper, a probabilistic roadmap planner algorithm with the multi robot path planning problem have been proposed by using the A* search algorithm in a dynamic environment. The whole process consists of two phases. In the first phase: Preprocessing phase, the work space is converted into the configuration space, constructing a probabilistic roadmap graph in the free space, and finding the optimal path for each robot using a global planner that avoids the collision with thestatic obstacles. The second phase: Moving phase, moves each robot in a prioritized manner from its starting point to its ending point through a near optimal path with avoiding collision with the moving obstacles and the other robots. A comparison has been done with the depth first algorithm to see the difference. The simulation results shows that choosing A* search algorithm affect positively the speed of the two phases together in comparison to the depth first search algorithm. 

Full paper is available at: http://research.ijcaonline.org/volume82/number7/pxc3892251.pdf

Citation

Safaa H Shwail, Alia Karim and Scott Turner. Article: Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS. International Journal of Computer Applications 82(7):29-34, November 2013. Published by Foundation of Computer Science, New York, USA

DOI:

10.5120/14130-2251

For more details on computing based research in Northampton go to: http://computingnorthampton.blogspot.co.uk/

MIT Robots Adapt and Collaborate Under Real World Conditions

MIT Robots Adapt and Collaborate Under Real World Conditions







"Real world" is a dangerous phrase to talk about when it comes to robots, because robots very seldom find themselves operating alone out there in wild and forlorn places like your living room or office. Autonomy in unstructured environments is an exceptionally difficult problem to tackle, and it gets even harder when you're dealing with multiple robots trying to collaborate on tasks in situations where they might not even be able to talk to each other reliably. MIT has been developing a control program that's able to coordinate multiple robots while dealing with significant uncertainty, and it's quite creative in how it goes about doing it.