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arXiv · 2110.15460

Human-Computer Interaction Glow Up: Examining Operational Trust and Intention Towards Mars Autonomous Systems

Abstract

Tactful coordination on earth between hundreds of operators from diverse disciplines and backgrounds is needed to ensure that Martian rovers have a high likelihood of achieving their science goals while enduring the harsh environment of the red planet. The operations team includes many individuals, each with independent and overlapping objectives, working to decide what to execute on the Mars surface during the next planning period. The team must work together to understand each other's objectives and constraints within a fixed time period, often requiring frequent revision. This study examines the challenges faced during Mars surface operations, from high-level science objectives to formulating a valid, safe, and optimal activity plan that is ready to be radiated to the rover. Through this examination, we aim to illuminate how planning intent can be formulated and effectively communicated to future spacecrafts that will become more and more autonomous. Our findings reveal the intricate nature of human-to-human interactions that require a large array of soft skills and core competencies to communicate concurrently with science and engineering teams during plan formulation. Additionally, our findings exposed significant challenges in eliciting planning intent from operators, which will intensify in the future, as operators on the ground asynchronously co-operate the rover with the on board autonomy. Building a marvellous robot and landing it onto the Mars surface are remarkable feats -however, ensuring that scientists can get the best out of the mission is an ongoing challenge and will not cease to be a difficult task with increased autonomy.

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BibTeXRIS

Thomas Chan, Jeremy Argueta, Jazlyn Armendariz, Allison Graham, Sarah Hwang, Basak Ramaswamy, So Young Kim, Scott Davidoff. 2021-10-28. Human-Computer Interaction Glow Up: Examining Operational Trust and Intention Towards Mars Autonomous Systems. https://doi.org/10.2514/6.2021-4117

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