Generative Planning for Hybrid Systems Based on Flow Tubes

When controlling an autonomous system, it is inefficient or sometimes impossible for the human operator to specify detailed commands. Instead, the field of AI autonomy has developed goal-directed systems, in which human operators specify a series of goals to be accomplished. Increasingly, the control of autonomous systems involves performing a mix of discrete and continuous actions. For example, a typical autonomous underwater vehicle (AUV) mission involves discrete actions, like get GPS and set sonar, and continuous actions, like descend and ascend, which involve continuous dynamics of the vehicle. Accordingly, we develop a hybrid planner that determines a series of discrete and continuous actions that achieve the mission goals. In this paper, we describe a novel approach to solving the generative planning problem for hybrid systems, involving both continuous and discrete actions. The planner, Kongming1 , incorporates two innovations. First, it employs a compact representation of all...

• Type: Conference
• Year: 2008
• Where: AIPS
• Authors: Hui X. Li, Brian C. Williams
• Keywords: AIPS 2008, Artificial Intelligence, Continuous Actions, Discrete Actions, Hybrid Flow Graph