Reactive Task Execution of a Mobile Robot

This thesis presents a novel control architecture, Samba, for reactive task execution. Reactive task execution implies goal-oriented and reactive properties from a robot and the ability to execute several tasks at the same time, also in a dynamic environment. These requirements are fulfilled in Samba by the representations of goals, intermediate results, and robot actions. The key idea in Samba is to produce continuously reactions for all the important objects in the environment. These reactions are represented as action maps, which are a novel representation for robot actions. An action map specifies for each possible action how preferable the action is from the perspective of the producer of the map. The preferences are shown by assigning a weight to each action. Tasks are executed by modifying and combining action maps. The tasks can be either reasoned by a higher layer or triggered by sensor data. Action maps, and the methods for modifying and combining them, enable executing tasks in parallel and considering the dynamics of the environment. Further, as the action maps are produced continuously from sensor data, the robot actions are based on the current state of the environment. Markers describe goals and intermediate results. They facilitate managing the complexity of the system. Markers describing intermediate results decompose the system vertically, into producers and consumers of data. Markers describing goals decompose the control system horizontally, into a Samba layer and a higher layer of reasoning tasks. Tasks flow via markers from the higher layer to the Samba layer. Markers are tested on a real robot equipped with a stereo gaze platform. Further, the Samba architecture is applied to playing soccer. Experiments were carried out in the 1997 and 1998 RoboCup competitions. These experiments show that the Samba architecture is a potential alternative for controlling a mobile robot in a dynamic environment.