English

Hindsight: Similarity-Based Analytics for Mars Rover Drive Retrieval

Human-Computer Interaction 2026-07-17 v1

Abstract

While Mars rover operators plan drives across hazardous Martian terrain and diagnose unexpected faults, the necessary information is distributed across separate systems and often reconstructed through manual correlation and memory. To address this challenge, we partnered with Mars rover operators at the NASA Jet Propulsion Laboratory to introduce Hindsight, a visual analytics system that unifies previously disparate rover drive data into a single workspace for search, comparison, and investigation. This paper presents a design study of the Hindsight application. The partnership revealed that operators reason about drives as holistic spatiotemporal episodes rather than discrete parameters. By externalizing operator intuition into an explicit visual query process, we argue that Hindsight transforms analysis into a structured, shareable workflow. Preliminary feedback from operators suggests Hindsight supports their ability to correlate terrain, telemetry, and fault events within a singleworkspace.

Cite

@article{arxiv.2607.16537,
  title  = {Hindsight: Similarity-Based Analytics for Mars Rover Drive Retrieval},
  author = {Luke Fiorante and Leslie Liu and Adam Xu and Xianmei Lei and Darwin Chiu and Krys Blackwood and Maggie Hendrie and Scott Davidoff and Santiago V. Lombeyda and Hillary Mushkin},
  journal= {arXiv preprint arXiv:2607.16537},
  year   = {2026}
}

Comments

In press for the 2026 IEEE Conference on Visualization (VIS 2026)