Human autonomy teaming-based safety-aware navigation through bio-inspired and graph-based algorithms

Abstract

In the field of autonomous robots, achieving complete precision is challenging, underscoring the need for human intervention, particularly in ensuring safety. Human Autonomy Teaming (HAT) is crucial for promoting safe and efficient human-robot collaboration in dynamic indoor environments. This paper introduces a framework designed to address these precision gaps, enhancing safety and robotic interactions within such settings. Central to our approach is a hybrid graph system that integrates the Generalized Voronoi Diagram (GVD) with spatio-temporal graphs, effectively combining human feedback, environmental factors, and key waypoints. An integral component of this system is the improved Node Selection Algorithm (iNSA), which utilizes the revised Grey Wolf Optimization (rGWO) for better adaptability and performance. Furthermore, an obstacle tracking model is employed to provide predictive data, enhancing the efficiency of the system. Human insights play a critical role, from supplying initial environmental data and determining key waypoints to intervening during unexpected challenges or dynamic environmental changes. Extensive simulation and comparison tests confirm the reliability and effectiveness of our proposed model, highlighting its unique advantages in the domain of HAT. This comprehensive approach ensures that the system remains robust and responsive to the complexities of real-world applications.

Keywords

Human autonomy teaming (HAT) / Robot path planning / Generalized Voronoi diagram (GVD) / Spatio-temporal graphs / Bio-inspired algorithms

CRediT authorship contribution statement

Timothy Sellers: Writing - review & editing, Writing - original draft, Visualization, Validation, Software, Methodology. Tingjun Lei: Writing - review & editing, Writing - original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis. Chaomin Luo: Writing - review & editing, Writing - original draft, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization. Zhuming Bi: Writing - review & editing, Supervision, Project administration, Conceptualization. Gene Eu Jan: Writing - review & editing, Supervision, Project administration, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

This research was partially supported by the Mississippi Space Grant Consortium under NASA EPSCoR RID grant.

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