Revisiting Formal Methods for Autonomous Robots: A Structured Survey

2025-09-24

AI Summary

This work addresses the lack of comprehensive, empirically grounded surveys on formal methods (FM) for sub-symbolic AI–driven robotic autonomous systems (RAS). Adopting a structured literature review methodology—including multi-database searching, optimized query strategies, double-blind screening, and collaborative assessment—we systematically analyze 2010–2023 publications. Our analysis reveals two emerging trends: rapid growth in formal synthesis techniques and probabilistic verification approaches for RAS. Crucially, we bridge a critical gap in prior surveys by explicitly characterizing FM practices—particularly specification modeling and verification—in sub-symbolic AI contexts. We propose a novel taxonomy for FM application in RAS, identify persistent technical challenges (e.g., scalability, uncertainty handling), and map adoption pathways across system layers. The findings provide evidence-based guidance for engineering trustworthy, formally assured autonomous robotics systems.

Technology Category

• Intelligent Robots: Other Foundations and Applications
• Cognitive Modeling & Cognitive Systems: Symbolic Representations
• Multiagent Systems: Other Foundations of Multi Agent Systems

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Methods, algorithms and applications for the development of semantic models, knowledge graphs and other forms of structured data models with machine-interpretable semantics

Abstract

This paper presents the initial results from our structured literature review on applications of Formal Methods (FM) to Robotic Autonomous Systems (RAS). We describe our structured survey methodology; including database selection and associated search strings, search filters and collaborative review of identified papers. We categorise and enumerate the FM approaches and formalisms that have been used for specification and verification of RAS. We investigate FM in the context of sub-symbolic AI-enabled RAS and examine the evolution of how FM is used over time in this field. This work complements a pre-existing survey in this area and we examine how this research area has matured over time. Specifically, our survey demonstrates that some trends have persisted as observed in a previous survey. Additionally, it recognized new trends that were not considered previously including a noticeable increase in adopting Formal Synthesis approaches as well as Probabilistic Verification Techniques.

Problem

• Surveying formal methods applications for robotic autonomous systems specification
• Investigating formal methods in sub-symbolic AI-enabled robotic systems evolution
• Analyzing trends in formal synthesis and probabilistic verification techniques

Innovation

• Structured survey methodology for literature review
• Categorization of formal methods for specification verification
• Identified trends in formal synthesis probabilistic verification