"Planning for unknown environments presents a number of technical challenges. The planner
must ensure robustness to unknown phenomena and manage unpredictable variation in
execution, all while operating in a capacity that maximizes its objective. Productivity in the
face of these challenges requires an integrated approach to planning and execution that is
capable of accomplishing goals, reacting to variation, and maximizing overall utility. We examine
this problem in the context of a Europa Lander concept mission. We model the problem as
a hierarchical task network, framing it as a utility maximization problem constrained on a
depletable energy resource. We propose a planning and execution framework that responds to
feedback using three techniques: (1) flexible execution, (2) periodic replanning, and (3) online
model parameter and utility updates. The efficacy of each of these techniques is examined
through simulation of a Europa Lander concept mission, showing higher utility achievement
compared to baseline approaches. We demonstrate that an integrated approach to planning
and execution that is grounded in replanning, utility maximization, and model parameter
updates will be an enabling technology for future tightly-constrained planetary surface
missions."

Using Flexible Execution, Replanning, and Model Parameter Updates to Address Environmental Uncertainty for a Planetary Lander

Space & Artificial Intelligence

technical paper

ECAI2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI, including:




**An extensive programme of workshops, tutorials, and invited speakers**

**The Prestigious Applications of Intelligent Systems conference (PAIS)**

**The Frontiers in AI track sessions**

**The Lab To Market event**

**The Women in AI time**

**The EU Challenges forum**

… and many more!

ECAI 2020

ECAI 2020 featured a full programme of technical papers, as well as many AI-related events of interest for researchers, students and all attendants who are interested on contemporary AI.

Daniel Wang

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Using Flexible Execution, Replanning, and Model Parameter Updates to Address Environmental Uncertainty for a Planetary Lander

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