— Areas of interest are picked out by the virtual honeybees (Image: Gustavo Olague)
Points of interest are analysed in 3D (Image: Gustavo Olague)
Copying the humble honeybee's foraging methods could give robots better 3D vision, researchers say. Robot explorers could identify points of interest by mimicking the way bees alert others of promising foraging spots.
Explorer bees report the location of a new food source, like an inviting flowerbed, by dancing on a special area of honeycomb when they return to the hive (see How vibes from dancing honeybees create a buzz on the dance floor).
A new type of stereoscopic computer vision system takes inspiration from this trick. It was developed by Gustavo Olague and Cesar Puente, from the Center for Scientific Investigation and Higher Education of Ensenada (CICESE) in Mexico.
A computer can generate 3D information using two cameras by comparing the view captured from different angles. It is, however, computationally intensive to do this for large scenes. Complicated statistical techniques can be used to pick out important features of a scene for further analysis, but this is still time-consuming.
The system developed by Olague and Puente is far simpler, they claim. It uses virtual honeybees to home in on potential points of interest, which can then be rendered in 3D. Simulated "explorer" bees are programmed to seek out features of potential interest in a 2D picture, based on criteria such as texture and edges. This can, for example, lead them to focus on a person or a prominent object in an otherwise empty room.
The honey bee software starts by randomly assigning explorer bees to different parts of an image. After identifying features of potential interest, these explorers recruit other virtual bees, known as "harvesters", to investigate in more detail. The explorers recruit harvesters in proportion to their interest in an area, meaning the most promising areas get the most attention.
If the harvesters also find the area interesting, they focus on it too. The system can then render it in 3D, based on all the bees' movements. This could eventually help a robot navigate or interact with its surrounding more efficiently.
"This algorithm can save time," Olague told New Scientist. "The harvesters are targeted by the explorers to look only at promising areas."
In testing, Olague and Puente used up to 8000 virtual explorer bees and 32,000 virtual harvesters. Before the end of 2006 they hope to use the honeybee vision system to help a mobile robot avoid obstacles.
Toby Breckon, a computer vision researcher at Cranfield University in the UK, says the approach has promise. "One of the big problems for stereo vision is that you have to search through the features in front of you," he says. "Bees have this almost built-in search algorithm that has the potential to help."
Breckon adds that the number of virtual bees could be adjusted for different situations. "A robot could use a small number of bees if it just needed to know where the walls of a corridor are, and then put in more bees to collect more detailed information," he says.
The research was presented at the 8th European Workshop on Evolutionary Computation in Image Analysis and Signal Processing in Budapest, Hungary, in April 2006, where it won the award for best paper.