From Hardware to Autonomy: A Cross-Layer Evidence Synthesis of Harsh-Environment Stressors and Failure Propagation in Field Robots
Field robots deployed in subsea, planetary, disaster-response, subterranean, and industrial environments frequently operate beyond nominal design assumptions, where environmental stressors degrade hardware, sensing, communication, and the assumptions underlying autonomous operation. Existing surveys typically organize harsh-environment robotics by application domain, limiting comparison of the cross-domain mechanisms through which exposure propagates into system-level failures. This survey addresses that gap through an environment-centered, evidence-coded synthesis of 348 records spanning field deployments, robotic experiments, component-level investigations, standards, and domain-specific surveys identified primarily in database searches (2015–May 2026), with supplementary sources. We classify environmental stressors into five categories, extreme physical, liquid/moisture-related, electromagnetic/radiation, chemical, and biological, with explicit evidence-basis labels distinguishing field observations, robotic tests, component evaluations, and proxy evidence, rather than assuming universal thresholds. Building on this taxonomy, we propose a qualitative synthesis lens, not a predictive or fitted model, connecting environmental exposure through hardware degradation or direct changes in operating conditions to autonomy-level assumption violations and mission-level reliability loss, applied to seven domain-based case syntheses spanning deep-sea, planetary, subterranean, nuclear, disaster-response, construction/mining, and defense robotics. We close with a three-tier benchmarking protocol, digital-twin simulation, hardware-in-the-loop testing, and controlled field validation, specifying the minimum reporting elements needed to make future robustness claims comparable across studies.
Authors
- Yutaka Watanobe (ORCID: https://orcid.org/0000-0002-0030-3859)
- Raihan Kabir (ORCID: https://orcid.org/0000-0003-2031-8836)
- Keitaro Naruse (ORCID: https://orcid.org/0000-0002-2029-2472)
- Leonard Chukwualuka Nnadi (ORCID: https://orcid.org/0009-0003-9429-2867)
- Md Obaydullah Al Numan (ORCID: https://orcid.org/0000-0002-6114-9306)
- Dake Ding (ORCID: https://orcid.org/0009-0005-3952-3698)
Institutions
- University of Aizu (JP)
Publication Details
- Journal
- Machines
- Published
- 2026-11-01
- DOI
- https://doi.org/10.3390/machines14111274
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00