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This paper gives a decision tree for processing on-board sensory data to aid autonomous trajectory determination for a robotic space vehicular system. The wealth of sensory data obtained from spacecraft automated sensors and multisource correlators forms the data segment of the data base. Decision making for these systems is aided by top-down AND/OR back-trackable tree searches and heuristics which are ideal for coding in a computationally intensive programming language. A strategy for autonomous trajectory determination and execution will enable space vehicles to be safe and smart.