Mobile machines are used to perform a variety of tasks. As an example, in an earthworking environment such as a mining site, mobile machines, e.g., off-road mining trucks, haul material throughout the site.
For repetitive tasks such as above, it is becoming advantageous and desirable to operate the mobile machines autonomously. The environment in which the trucks operate may be harsh, and more efficient operations may be attained if the human fatigue factor is eliminated.
As an example of using off-road mining trucks autonomously, U.S. Pat. No. 5,612,883, issued to Shaffer et al., provides an exemplary disclosure of a system for autonomous operations of mobile machines. In this patent, Shaffer et al. discloses a fleet of off-road mining trucks operating autonomously at a mining site. Parameters such as position determination, navigation, path planning, and machine control are performed without the aid of human operators.
An important factor in enabling a mobile machine to operate autonomously is the ability to detect obstacles in the machine's path of travel, and to respond in an acceptable manner when obstacles are detected. In the above example, Shaffer et al. teaches a system and method for detecting obstacles in the path of a mobile machine.
However, obstacle detection systems must operate under complex and constantly changing environments. In the autonomous, off-road mining truck example described by Shaffer et al., the trucks must navigate winding and curving roads under harsh environmental conditions. Frequently, normal obstacle detection procedures are interrupted by the need to maneuver around previously detected obstacles, thus requiring the truck to be able to detect obstacles at close range in confined areas. Under these changing conditions, no single obstacle detection system can provide optimal results at all times.
Attempts have been made to combine various obstacle sensors into a packaged obstacle detection system. For example, in U.S. Pat. No. 5,170,352, McTamaney et al. discloses an obstacle detection system using touch sensors, infrared sensors, ultrasonic sensors, laser sensors, and vision sensors. This variety of sensors provide redundant operation as an autonomous vehicle moves about. However, the various sensors, by the nature of their individual characteristics, will differ in their interpretations of the obstacle being detected. For example, an infrared sensor and an ultrasonic sensor may detect the same obstacle, but information such as location, size, and shape of the obstacle may differ widely between the two sensors. Some of these differences may be attributed to external factors such as ambient light and the angle of detection. A method and system is needed to compensate for the differences in the characteristics of the sensors and the various external factors, and to evaluate the data received from each sensor to determine the presence of an obstacle in an optimal manner.
The present invention is directed to overcoming one or more of the problems as set forth above.