Paul Boughton
A team of engineers from the University of La Laguna (ULL) in the Canary Islands has designed the Verdino, a self-steering vehicle that can sense the road surface using a technique called Ant Colony Optimisation (ACO). This method is based on the behaviour used by ants to find the shortest way between their ant hill and sources of food.
The study's lead author, Rafael Arnay, from the ULL's Department of Systems and Automatic Engineering and Computer Architecture and Technology says that the ACO algorithms are used to resolve problems of combinatory optimisation and were inspired directly by ants. In nature, ants leave a trail of pheromones as they move, which can be detected and followed by other members of the colony. The pheromones evaporate over time, which means that the path used by those ants that move to and from the food source over the shortest distance is the most deeply reinforced by these chemical substances, and so is the one chosen by the other ants.
Arnay states: "The ACO technique is based, similarly, on a colony of artificial ants; in other words, computational agents that work cooperatively and communicate with each other by means of artificial pheromone trails." This technique allows the Verdino to keep to the correct path along the road without the need for any driver.
The prototype looks like a golf buggy but it incorporates a camera that gathers the visual data necessary to apply the algorithms, as well as an internal control system that processes the data in real time. The Verdino is programmed to travel along unstructured roads without lines painted on the surface, or with irregular edges caused by encroachment by soil or vegetation.
Engineers are currently testing the vehicle with a view to it being used as an internal transport system to link 25 housing units and a visitor centre in a bioclimatic housing development being built by the Technological and Renewable Energy Institute in the south of Tenerife; they describe the first results as "very promising."
The researchers believe the self-guided system could be commercialised and used in vehicles to be used in places such as historical town centres, tourist complexes, exhibition or sporting venues, shopping centres and industrial estates, and could even be used within remote security systems or in adapted cars for elderly or disabled people.
Ant Colony Optimisation
The study's lead author, Rafael Arnay, from the ULL's Department of Systems and Automatic Engineering and Computer Architecture and Technology says that the ACO algorithms are used to resolve problems of combinatory optimisation and were inspired directly by ants. In nature, ants leave a trail of pheromones as they move, which can be detected and followed by other members of the colony. The pheromones evaporate over time, which means that the path used by those ants that move to and from the food source over the shortest distance is the most deeply reinforced by these chemical substances, and so is the one chosen by the other ants.
Arnay states: "The ACO technique is based, similarly, on a colony of artificial ants; in other words, computational agents that work cooperatively and communicate with each other by means of artificial pheromone trails." This technique allows the Verdino to keep to the correct path along the road without the need for any driver.
The prototype looks like a golf buggy but it incorporates a camera that gathers the visual data necessary to apply the algorithms, as well as an internal control system that processes the data in real time. The Verdino is programmed to travel along unstructured roads without lines painted on the surface, or with irregular edges caused by encroachment by soil or vegetation.
Engineers are currently testing the vehicle with a view to it being used as an internal transport system to link 25 housing units and a visitor centre in a bioclimatic housing development being built by the Technological and Renewable Energy Institute in the south of Tenerife; they describe the first results as "very promising."
The researchers believe the self-guided system could be commercialised and used in vehicles to be used in places such as historical town centres, tourist complexes, exhibition or sporting venues, shopping centres and industrial estates, and could even be used within remote security systems or in adapted cars for elderly or disabled people.
Ant Colony Optimisation
