Universiti Teknologi Malaysia Institutional Repository

A particle swarm optimization approach to robotic drill route optimization

Zainal Abidin, Amar Faiz and Ibrahim, Zuwairie and Husain, Abd Rashid and A., Adam and Z., Md. Yusof and I., Ibrahim (2010) A particle swarm optimization approach to robotic drill route optimization. In: AMS2010: Asia Modelling Symposium 2010 - 4th International Conference on Mathematical Modelling and Computer Simulation, 2010, Kota Kinabalu, Malaysia.

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Official URL: http://dx.doi.org/10.1109/AMS.2010.25


Most of the operational time of a PCB Robotic Drill is spent on moving the drill bit between the holes. This operational time can be kept at a minimal level by optimizing the route taken by the robot. An optimized route translates to a minimal cost of operating the robot. This paper proposes a new model that implements Particle Swarm Optimization (PSO) in order to find optimized routing path when using the PCB Robotic Drill. The main task of the PCB Robotic Drill is to drill holes at Printed Circuit Board (PCB). This PCB Robotic Drill will route the drill site by moving the drill bit along Cartesian axes from it’s initial position. Then, the drill bit will return back to the initial position. The drill route consists of a number of potential locations where the holes are going to be drilled. As the number of holes required increases so thus does the complexity to find the optimized route. The proposed model can be used to solve this complex problem with minimal computational time. The result of a case study indicates that the proposed model is capable to find the shortest path for the robot to complete its task. Thus concluded the proposed model can be implemented in any drill route problems.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:kiv record
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:27097
Deposited By: Mrs Liza Porijo
Deposited On:27 Jul 2012 03:41
Last Modified:11 Oct 2017 08:05

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