botics, Inc., sees the method as a boon for everyday use. Although robots are now used in applications such as delivering hospital sup- plies, they require training to familiarize them with their particular environment, possibly relying on effective but expensive laser rangefinders. Pirjanian and his colleagues propose an alternative they call visual simultaneous localization and mapping (VSLAM), which might be suitable for consumer products because it uses inexpensive video cameras.
A VSLAM robot gets its bearings in bootstrap fashion. It begins by taking pictures of recognizable features like furniture, and holds them in a database. Initially the robot estimates the landmarks’ loca- tions and its own through wheel odometry.As it continues mapping, it compares whatever its camera registers to its database.When a match occurs, the unit uses probabilistic methods to recalculate the land- marks’ position and its own. The interplay between these upgrades steadily refines the robot’s knowledge, leading to a final accuracy of about 10 centimeters (4 inches) in its position, and 5 degrees in its direction of motion. Unlike robots that find their way by means of a fixed internal map, VSLAM can also deal with change: If there is enough alteration in its surroundings that no landmarks are recog- nized, the robot finds new ones and updates its map.
Artificial vision has become so fine-tuned that it can be trusted at high speeds and when lives are at stake.The small robot cave explorers deployed in the 2001–2002 U.S. campaign in Afghanistan show the military potential, and the Department of Defense (DoD) foresees more demanding applications.Through DARPA, the DoD is offering $1 million to anyone who can create a self-guided unit for desert warfare.The prize will be awarded in 2004 for a vehicle that can trek through the Mojave Desert from Barstow, California to a location near Las Vegas on its own.To cover a distance of about 320 kilometers (200 miles) within the allotted time of 10 hours, the unit must maintain an average speed of at least 32 kilometers per hour (20 miles per hour).
Other high-speed applications aimed at improving automobile safety through the use of intelligent artificial vision have been under development at Carnegie Mellon University and elsewhere. In one