| This thesis provides a method for compressing the information provided by Jet Propulsion Laboratory Mars rover obstacle sensors by creating an approximate map of the terrain around the vehicle. This thesis demonstrates that this method provides adequate information for a human operator to negotiate complex obstacle fields.; By dividing the area around the vehicle into regions and classifying each region as to how dangerous (impassable) it is, the sensor data can be accumulated with minimal overhead. The terrain in each region has a number between zero and one, with zero meaning completely passable and one meaning completely impassable. A continuum of possible values between the extremes classifies in the sense of fuzzy set theory. This process allows obstacles to be represented in the map as an abstraction of the data instead of being arduously tracked individually, requiring much memory and complex processing. The map concept is also valuable in the respect that via translation of the vehicle, information is passed to regions without direct sensor inputs. This allows the system to track obstacles to the side and to some extent behind the vehicle. The system, therefore, could potentially deal with complex situations where this information would be valuable, such as a situation where it needs to recognize and back out of a trap.; This thesis includes the development of the approximate mapping algorithm, explanation of the integration with a test-bed vehicle, demonstration of the algorithm using the test-bed vehicle, and ground work for the development of an automatic decision making scheme, which will constitute the continuing research effort. |
