Increased mars rover autonomy using AI planning, scheduling and execution

  • Estlin T
  • Gaines D
  • Chouinard C
 et al. 
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This paper presents technology for performing autonomous commanding of a planetary rover. Through the use of AI planning, scheduling and execution techniques, the OASIS autonomous science system provides capabilities for the automated generation of a rover activity plan based on science priorities, the handling of opportunistic science, including new science targets identified by onboard data analysis software, other dynamic decision-making such as modifying the rover activity plan in response to problems or other state and resource changes. We first describe some of the particular challenges this work has begun to address and then describe our system approach. Finally, we report on our experience testing this software with a Mars rover prototype.

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  • Tara Estlin

  • Daniel Gaines

  • Caroline Chouinard

  • Rebecca Castano

  • Benjamin Borastein

  • Michele Judd

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