Source-linked AI summary
A Taxonomy on Collective Awareness
Guillermo GP-Lenza, Miguel Fernandez-Cortizas, Martín Molina, Ricardo Sanz, Pascual Campoy
TL;DR
Multi-robot coordination depends on aligned representations of teammates, the environment, and mission state, yet Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness are often treated as interchangeable. The paper develops a two-axis taxonomy and uses a heterogeneous Search and Rescue scenario to ground its distinctions. It concludes that the three types form a layered hierarchy with distinct content and distribution requirements, offering a conceptual foundation for principled design and comparison.
Problem
Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness are often used interchangeably despite imposing distinct coordination requirements.
Source: §1 · pp. 2–3Method
The article develops a taxonomy organized by object of awareness and awareness distribution, illustrating its categories with a heterogeneous aerial-and-ground robot Search and Rescue scenario.
Source: §1 · p. 3, §3.1 · pp. 10–11Results
The taxonomy establishes MA, SSA, and TSA as a layered hierarchy with distinct awareness content and distribution requirements, rather than interchangeable labels.
Source: §4 · pp. 13–14Takeaways & Limitations
The taxonomy provides a conceptual foundation for more principled design and meaningful comparison of multi-robot coordination approaches.
Source: §4 · pp. 13–14The taxonomy’s requirements remain to be formalized as verifiable specifications, instantiated in architectures, and empirically evaluated in deployed systems.
Source: §4 · p. 14
Abstract
from arXiv · showhide
As robotic teams tackle increasingly complex tasks in dynamic and unstructured environments, effective coordination requires agents to maintain accurate, aligned representations of their environment, teammates, and mission state. We argue that Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness --- three concepts widely invoked in the multi-robot systems literature --- are not interchangeable: they form a containment hierarchy in which each type subsumes the previous in scope, and span a distribution spectrum from fully individualized understanding (MA) to fully uniform understanding (SSA), with TSA occupying a mixed position. We establish this through a two-dimensional taxonomy organized along the object of awareness and awareness distribution axes. Treating these terms as synonyms obscures the precise coordination requirements each imposes on a robotic system. A Search and Rescue case study with heterogeneous aerial and ground robots grounds each taxonomy position in concrete coordination requirements. These findings provide a conceptual foundation for principled specification, design, and comparison of collective awareness in multi-robot systems.
1 Introduction
Coordination in multi-robot systems depends on agents maintaining accurate representations of their environment, teammates, and mission state. The paper argues that Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness have distinct requirements and develops a framework to clarify them.
1 Introduction
- Agents need accurate representations of the environment, teammates, and evolving mission state to anticipate and complement one another’s actions during coordination.Multi-robot teams can vary in composition, communication, and objectives.Source: §1 · p. 2
- Situation Awareness is grounded in perception, comprehension, and projection, while collective extensions characterize how team members align understanding for coordination.Recent work also frames awareness as real-time understanding of sensory flows through valid inferences about environmental objects.Source: §1 · pp. 2–3
- The paper identifies two underspecified questions: how awareness types differ and relate, and what definitions capture their roles in multi-robot coordination.The literature often uses the three terms interchangeably despite their differing knowledge scope and uniformity requirements.Source: §1 · p. 3
- The article develops a conceptual framework and two-axis taxonomy, illustrating awareness classifications with a heterogeneous aerial-and-ground robot Search and Rescue scenario.The taxonomy uses awareness distribution and object of awareness as its axes.Source: §1 · p. 3
2 Awareness in Multi-Robot Systems
The section reviews Mutual Awareness, Shared Situational Awareness, and Team Situational Awareness as overlapping concepts with different accounts of individual, shared, and team-level understanding. Their definitions vary in whether awareness is directional, shared across requirements, or distributed according to team roles and processes.
2 Awareness in Multi-Robot Systems
- The section reviews these three collective-awareness forms and points readers to a table of representative definitions.The article preserves the source literature’s distinction between “Situation Awareness” and “Situational Awareness.”Source: §2 · p. 3, Table 1 · p. 4
2.1 Mutual Awareness
- Mutual Awareness concerns understanding teammates’ intentions, beliefs, and activities, and can be directional or asymmetric when observation is not reciprocal (She and Li (2017); Villa et al. (2008)).Other accounts connect mutual responsiveness to shared cooperative goals (Bratman (1992)).Source: §2.1 · p. 5
2.2 Shared Situational Awareness
- Shared Situational Awareness is the overlap in team members’ situation-awareness requirements, with shared information focused on critical elements to limit communication overload (Endsley Mica R. (2001); Sepp¨anen, M¨akel¨a, Luokkala, and Virrantaus (2013)).Another account describes it as an updated, integrated mission representation built from shared information (Salas, Stout, and Cannon-Bowers (1995)).Source: §2.2 · p. 5
2.3 Team Situational Awareness
- Team Situational Awareness accounts range from overlapping individual SA states (McNeese, Demir, Cooke, and She (2021)) to team processes that cannot be reduced to summed individual awareness (Salas, Prince, et al. (1995a)).Other accounts describe a partly shared, partly distributed model that supports anticipation of future states (Artman and Garbis (1998)).Source: §2.3 · pp. 5–6
3 Taxonomy of Collective Awareness
The taxonomy distinguishes collective-awareness requirements by what agents must know and how uniformly that knowledge is distributed. A heterogeneous search-and-rescue team illustrates how mutual, shared, and team situational awareness occupy distinct positions across these axes.
3 Taxonomy of Collective Awareness
- The taxonomy uses object of awareness and awareness distribution to characterize distinct information-exchange and coordination requirements, grounded in a heterogeneous search-and-rescue mission.The example includes UAVs and UGVs coordinating across overlapping deployment, reconnaissance, rescue, and monitoring phases.Source: §3 · pp. 6, 8
3.1 Object of Awareness
- Shared situational awareness covers role-intersection requirements, including peer states and critical external mission factors; team situational awareness adds role-specific awareness to this shared foundation.In the example, survivor locations and status are shared, while UAVs track landing zones and wind and UGVs track debris and terrain traversability.Source: §3.1 · pp. 10–11
3.2 Awareness Distribution
- Mutual awareness is individualized, shared situational awareness requires aligned understanding of critical elements, and team situational awareness combines shared and role-specific awareness.The distribution axis ranges from agents forming individualized understandings to all agents maintaining the same understanding, with team awareness allowing both.Source: §3.2 · pp. 11–12
3.3 Synthesized Definitions
- The synthesized definitions distinguish mutual awareness of teammates’ internal states, shared awareness of required mission elements, and team awareness encompassing both shared and role-specific elements.In the search-and-rescue example, team awareness includes peer-state awareness, shared mission-critical awareness, and role-specific environmental knowledge; the latter is not captured by mutual or shared awareness alone.Source: §3.3 · pp. 12–13
4 Conclusions
The article presents a conceptual framework clarifying collective-awareness terminology in multi-robot coordination, distinguishing MA, SSA, and TSA as a layered hierarchy with distinct requirements. A Search and Rescue case study illustrates how mission phases require different awareness specifications.
4 Conclusions
- The Search and Rescue case study shows that mission phases demand different combinations of awareness specifications.These specifications reflect the requirements of MA, SSA, and TSA.Source: §4 · p. 13
- MA, SSA, and TSA form a layered hierarchy with distinct awareness-distribution and content requirements, rather than interchangeable labels.MA concerns awareness of teammates’ beliefs, plans, and states; SSA adds shared understanding of mission-critical environmental elements; TSA combines shared and role-specific awareness.Source: §4 · pp. 13–14
- Future work should formalize the taxonomy’s requirements as verifiable specifications, develop architectures that instantiate them, and evaluate their effects on deployed coordination performance.The taxonomy provides a conceptual foundation for more principled design and comparison of multi-robot coordination approaches.Source: §4 · p. 14
Declarations
The authors report funding and support, no relevant competing interests, and the applicable publication, ethics, and availability declarations. All authors contributed to the study conception and design.
Declarations
- The work acknowledges project funding and predoctoral research support for the first author.The support includes CORESENSE, INSERTION, RETMUR, and the Community of Madrid predoctoral program.Source: Declarations · p. 14
- The authors declare no relevant competing interests; ethics approval, consent to participate, and data, materials, and code availability are listed as not applicable.All authors consented to publication.Source: Declarations · pp. 14–15
- All authors contributed to study conception and design, while Guillermo GP-Lenza performed material preparation, literature review, and analysis and drafted the manuscript.All authors commented on prior versions and approved the final manuscript.Source: Declarations · p. 15