Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Automatic route guidance vehicle
Reexamination Certificate
1999-02-22
2001-06-26
Louis-Jacques, Jacques H. (Department: 3661)
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Automatic route guidance vehicle
C701S025000, C701S026000, C701S301000, C180S168000, C180S169000, C340S902000, C340S903000, C340S436000, C246S16700M
Reexamination Certificate
active
06253128
ABSTRACT:
TECHNICAL FIELD
The present invention relates to an apparatus for guiding unmanned vehicles.
BACKGROUND ART
Unmanned, off-road dump trucks (referred to below as unmanned dump trucks) are widely used in mines to release personnel from arduous labor, lower production costs, and to reduce fuel consumption.
These unmanned dump trucks are equipped with the following so as to automate their motion: a device for measuring travel position using dead reckoning and GPS, a storage device for storing course data, and a control device for controlling the movement of the unmanned dump truck based on the travel position and course data.
A widely used method for preparing course data is a teaching system wherein the unmanned dump truck is actually operated and its travel positions are stored.
The course data are generally prepared with a teaching system for recording the positions of the dump truck over time while the unmanned dump truck is actually operated.
The course data prepared by the teaching system show the conditions of actual vehicle travel. Consequently, the contents thereof include position data satisfying travel speed, acceleration and deceleration and the lateral acceleration, which were actually possible for the vehicle to run under the conditions of the course in that instance. Furthermore, the course data include elements which are difficult to find through automatic calculations, such as the appropriate deceleration for an anticipated curve or acceleration for an anticipated upward grade. Moreover, the teaching system is easy for an operator to understand, since the operator just drives the vehicle.
For these reasons, the procedure for preparing course data with a teaching system is widely used.
Meanwhile, the technique of combining the teaching system with an offline system of preparing the course on a computer, according to the complexity of the course, has also been proposed (Japanese Patent Laid-open No. 8-101712).
In this way, the teaching system handles simple portions, such as straight sections, offline and handles complex portions where interference is likely in the vehicle.
Course data prepared by the teaching show the path actually traveled by the unmanned dump truck.
However, the vehicle in operation may not necessarily travel on the same course that was taught as a result of errors in position measurement or errors in the control of the vehicle using the measured positions.
For this reason, there is a risk that the vehicle, which traveled in the course area during the teaching operation, may travel outside of the course area and have an accident while repeating the actual course.
During teaching, the operator may anticipate the errors when operating the vehicle, but this is certainly not a perfect system. Furthermore, when the vehicle must pass other vehicles or when the area traveled is narrow, it is a difficult job to perform teaching for anticipating errors during travel and for avoiding interference with other vehicles and areas outside the course area.
The present invention was made in view of these circumstances and it is an object of the present invention to provide an interference prediction apparatus for unmanned vehicles which can predict interference of an unmanned vehicle when the vehicle is guided by course data prepared through teaching or the like.
SUMMARY OF THE INVENTION
The first invention is an interference prediction apparatus for unmanned vehicles, which is applied to an unmanned vehicle guided through a course area on the basis of travel position and course data, comprising: means for inputting the form of the course area; means for preparing the course data; means for estimating error of travel position when the unmanned vehicle is traveling according to the course data; and means for predicting the interference of the unmanned vehicle with areas outside of the course area on the basis of the estimated error.
With the first invention, errors in travel position during the unmanned vehicle's travel according to the course data are estimated, and interference of the unmanned vehicle with areas outside the course area is predicted on the basis of this error.
Consequently, interference of the unmanned vehicle with areas outside the course area can be predicted before the unmanned vehicle actually travels according to the prepared course data. As a result, it becomes possible to take steps, such as changing the course data and reteaching, to avoid actual interference of the unmanned vehicle.
The second invention is an interference prediction apparatus for unmanned vehicles, which is applied to unmanned vehicles guided on the basis of travel position and course data on different lanes in a course area, comprising: means for inputting the form of the course area; means for preparing the course data; means for estimating error of travel position when one unmanned vehicle is traveling according to its course data, while estimating error of travel position when another vehicle is traveling according to its course data; and means for predicting interference of the unmanned vehicle with areas outside of the course area and the interference of the vehicle with the other vehicle on the basis of the estimated error values.
With this second invention, it is possible to predict the interference of a vehicle with areas outside the course area, as well as the interference of a vehicle with another vehicle when a plurality of unmanned vehicles are traveling within the course area at the same time.
In the third invention, the means for predicting interference in the first invention comprises: means for estimating the zone wherein the unmanned vehicle is located based on the width of the unmanned vehicle, the course data, and the estimated error; and means for determining that the edge of the course area is within the zone in which the unmanned vehicle is located.
With the third invention, the zone in which the unmanned vehicle is present is estimated and this zone is used as the standard for determining whether interference will occur.
In the fourth invention, the means for predicting interference in the second invention comprises: means for estimating the zones wherein each of the unmanned vehicles is present based on the width of each of the unmanned vehicles, the course data of each vehicle, and the estimated error; and means for determining whether the edge of the course area is within this zone wherein the unmanned vehicle is present and determining whether the zones overlap.
With the fourth invention, the zones wherein a vehicle and another vehicle are present are each estimated and interference between the vehicles and the edge of the course area is predicted on the basis of those zones, while interference between the vehicle and another vehicle is predicted on the basis of the zones.
In the fifth invention, the means for predicting interference in the first invention comprises: means for establishing the zone within the course area where positions in the course data may not be present, on the basis of the estimated error, the course area, and the width of the unmanned vehicle, and means for determining that positions in the course data are present within the zone.
With the fifth invention, the zone where the positions in the course data are not present within the course area is established, instead of the zone wherein the vehicle is located, and interference between the vehicle and the edge of the course area is predicted when positions in the course data are present in this zone.
In the sixth invention, the means for predicting interference in the second invention comprises: means for establishing the zone in the course area where positions in the course data for a vehicle may not be present, and the zone in the course area where positions in the course data for another vehicle may not be present, on the basis of the estimated error, the course area, the central position of the course area, and the widths of the vehicles; and means for determining that corresponding positions in the course data are present in the zones.
With the sixth invention, a
Kageyama Masato
Kuromoto Kazunori
Okawa Yukio
Komatsu Ltd.
Louis-Jacques Jacques H.
Varndell & Varndell PLLC
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