pith. sign in

arxiv: 2605.06662 · v1 · submitted 2026-05-07 · 💻 cs.RO

Multi-Robot Coordination in V2X Environments

John Pravin Arockiasamy , Alexey Vinel This is my paper

Pith reviewed 2026-05-08 08:36 UTC · model grok-4.3

classification 💻 cs.RO
keywords multi-robot coordinationV2X communicationvulnerable road usersdecentralized cooperationrobot awareness servicemaneuver coordinationfinite-state modelroad crossing assistance
0
0 comments X

The pith

Two new robot services built on vehicle communication standards enable decentralized coordination to assist pedestrians crossing roads.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper develops a communication approach that lets social robots share awareness and adjust their actions together in urban traffic without needing central control or pre-set pairings. It defines two services, one for robots to broadcast their roles and detect nearby people including those without devices, and another for quick coordination of their movements during events. A real demonstration shows a humanoid robot and a quadruped robot using a fixed set of states to help a pedestrian cross safely. Simulations indicate the method groups unprotected road users for safety while cutting extra messages that would otherwise overload the network. If successful, robots could join connected traffic systems as active helpers rather than separate entities.

Core claim

The paper establishes that Robot Awareness Service (RAS) and Robot Maneuver Coordination Service (RMCS), implemented via dedicated messages, support role-aware awareness of robots and non-equipped users plus event-driven maneuver coordination. This setup produces deterministic multi-robot behavior under a formally specified finite-state model, as shown in a live test where a humanoid and quadrupedal robot assist a pedestrian during road crossing. Complementary evaluations confirm that the awareness service clusters vulnerable road users in mixed environments and lowers channel load by reducing redundant transmissions from equipped participants.

What carries the argument

The Robot Awareness Service (RAS) and Robot Maneuver Coordination Service (RMCS) that extend existing vehicle communication standards to provide role-based awareness and low-latency decentralized maneuver coordination without prior pairing or central infrastructure.

If this is right

  • Non-equipped pedestrians become part of cooperative awareness through robot mediation.
  • Redundant transmissions drop and overall channel load decreases in mixed traffic.
  • Finite-state models deliver deterministic coordination for safety-critical tasks.
  • The services create a scalable path to embed cooperative robots into connected mobility systems.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same coordination model could scale to teams of robots performing delivery or patrol duties in pedestrian zones.
  • Robot actions coordinated this way might indirectly shape nearby vehicle paths for smoother traffic flow.
  • Further trials in dense or adverse conditions would test whether latency stays low enough for real-time use.

Load-bearing premise

The services can reliably incorporate non-equipped pedestrians and deliver low-latency coordination in complex real urban settings without any pre-established connections or centralized oversight.

What would settle it

A field trial in a busy urban intersection showing either failed robot coordination during pedestrian assistance or message delays exceeding safe thresholds.

Figures

Figures reproduced from arXiv: 2605.06662 by Alexey Vinel, John Pravin Arockiasamy.

Figure 1
Figure 1. Figure 1: Structure of the RAM framework. RobotLeaderFollowerOperationContainer followerBreakupInfo followerLeaveInfo followerJoinInfo robotType RobotStatusContainer jobType currentTaskStatus healthStatus operationMode helpStatus view at source ↗
Figure 2
Figure 2. Figure 2: Robot status container (left) and Robot coordination view at source ↗
Figure 3
Figure 3. Figure 3: Structure of the RMCM framework. FollowerManeuverContainer jobAdviceID OperationMode intersectionReferenceID roadSegmentReferenceID targetFollowerStationID LeaderManeuverContainer requestID slaveAdviceList followerAdviceList followerAdvice jobAdvice jobType taskType jobAdviceResponseList jobPerformedInLane jobAdviceResponse jobAdvice Followed view at source ↗
Figure 4
Figure 4. Figure 4: Leader and follower maneuver containers in the RMCM view at source ↗
Figure 5
Figure 5. Figure 5: FSM governing decentralized multi-robot coordination view at source ↗
Figure 6
Figure 6. Figure 6: Five-stage multi-robot coordination using V2X OBUs (white boxes) for pedestrian crossing assistance with RAM and RMCM. follower executes ManeuverCompleted. Across N = 5 trials, initialPos yielded Tneg = 0.074 ± 0.015 s and Texec ≈ 0.50 s (TTMCT = 0.574 ± 0.015 s); the pedestrian￾escort Move maneuver yielded Tneg = 0.129 ± 0.102 s and Texec = 21.60 s (TTMCT = 21.729 ± 0.102 s), demonstrating stable and low-… view at source ↗
Figure 7
Figure 7. Figure 7: Observation coverage ratio (OBS) for non-V2X pedes view at source ↗
read the original abstract

This paper presents a Vehicle-to-Everything (V2X) communication framework that enables decentralized cooperation among social robots operating in complex urban traffic environments. Building on ETSI Cooperative Awareness and Maneuver Coordination services, the framework introduces two robot-centric facility-layer services: the Robot Awareness Service (RAS) and the Robot Maneuver Coordination Service (RMCS), realized through the Robot Awareness Message (RAM) and the Robot Maneuver Coordination Message (RMCM), respectively. RAS enables role-aware, task-oriented robot awareness while integrating externally detected Vulnerable Road Users (VRUs), including non-V2X pedestrians, into cooperative awareness. RMCS supports event-driven, low-latency coordination of robot maneuvers under explicitly established roles, without centralized infrastructure or prior pairing. A real-world proof of concept demonstrates deterministic multi-robot coordination between a humanoid robot and a quadrupedal robot assisting a pedestrian during a road-crossing scenario, governed by a formally specified finite-state coordination model. Complementary simulations evaluate robot-mediated VRU clustering in mixed V2X environments, showing that RAS-based clustering integrates non-V2X VRUs in safety-critical areas while reducing redundant transmissions from V2X-enabled VRUs, thereby lowering channel load. Together, the proposed services provide a scalable and standards-aligned foundation for integrating cooperative robots into future Connected, Cooperative, and Automated Mobility ecosystems.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 3 minor

Summary. The paper proposes a V2X framework extending ETSI Cooperative Awareness and Maneuver Coordination services with two new robot-centric facility-layer services: the Robot Awareness Service (RAS) using Robot Awareness Messages (RAM) and the Robot Maneuver Coordination Service (RMCS) using Robot Maneuver Coordination Messages (RMCM). These enable role-aware awareness that integrates non-V2X VRUs and event-driven decentralized maneuver coordination without prior pairing or central infrastructure. A formally specified finite-state coordination model governs the interactions. The central claims are supported by a real-world proof-of-concept experiment demonstrating deterministic coordination between a humanoid robot and a quadrupedal robot assisting a pedestrian in a road-crossing scenario, plus complementary simulations showing reduced channel load and effective VRU clustering in mixed V2X environments.

Significance. If the determinism and integration claims hold under realistic noise, the work supplies a standards-aligned, decentralized mechanism for incorporating social robots into C-ITS ecosystems. This could improve VRU safety in urban traffic by allowing robots to participate in cooperative awareness and maneuvers without requiring dedicated infrastructure or pre-established pairings. The provision of a formally specified FSM and the dual POC-plus-simulation evaluation are positive elements that strengthen falsifiability.

major comments (2)
  1. [Section 4] Section 4 (Proof-of-Concept Experiment): The claim that the real-world demonstration executed the finite-state coordination model deterministically is load-bearing for the central contribution, yet no quantitative verification is supplied. Transition logs, per-state timing histograms, packet-loss counts, or deviation metrics comparing FSM-predicted actions to observed robot trajectories under sensor latency and V2X packet loss are absent, leaving open whether the hardware behavior matched the model or was only qualitatively similar.
  2. [Section 3.2] Section 3.2 (RMCS and Role Establishment): The assertion that RMCS achieves low-latency coordination 'without centralized infrastructure or prior pairing' rests on the assumption that role negotiation via RMCM messages succeeds reliably in the presence of wireless contention and perception errors. No analysis or simulation of message-loss-induced state divergence or fallback behavior is provided, which directly affects the scalability claim for complex urban environments.
minor comments (3)
  1. [Abstract] The abstract introduces the acronyms RAS, RMCS, RAM, and RMCM without immediate expansion, which reduces readability for readers unfamiliar with the ETSI extensions.
  2. [Section 5] Figure captions and simulation parameter tables would benefit from explicit statements of the channel model (e.g., packet error rate, latency distribution) used to generate the reported channel-load reductions.
  3. [Section 2] A brief comparison table placing RAS/RMCS against existing ETSI CA/MCM extensions or other robot-V2X proposals would clarify the incremental novelty.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments, which help clarify the presentation of our contributions. We address each major comment below and indicate the revisions we will make to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Section 4] Section 4 (Proof-of-Concept Experiment): The claim that the real-world demonstration executed the finite-state coordination model deterministically is load-bearing for the central contribution, yet no quantitative verification is supplied. Transition logs, per-state timing histograms, packet-loss counts, or deviation metrics comparing FSM-predicted actions to observed robot trajectories under sensor latency and V2X packet loss are absent, leaving open whether the hardware behavior matched the model or was only qualitatively similar.

    Authors: We agree that quantitative verification of the FSM execution is essential to substantiate the determinism claim. The current Section 4 presents the experiment through qualitative description and video evidence. In the revised manuscript we will add the requested quantitative data extracted from the experiment logs: full state-transition sequences with timestamps, per-state timing histograms, measured V2X packet-loss rates, and trajectory deviation metrics (position and velocity errors) between FSM-predicted actions and observed robot behavior, explicitly accounting for sensor latency and communication delays. revision: yes

  2. Referee: [Section 3.2] Section 3.2 (RMCS and Role Establishment): The assertion that RMCS achieves low-latency coordination 'without centralized infrastructure or prior pairing' rests on the assumption that role negotiation via RMCM messages succeeds reliably in the presence of wireless contention and perception errors. No analysis or simulation of message-loss-induced state divergence or fallback behavior is provided, which directly affects the scalability claim for complex urban environments.

    Authors: The formally specified FSM in Section 3.2 already incorporates explicit states and transitions for message loss, role re-negotiation, and fallback to safe maneuvers to prevent divergence. Nevertheless, we acknowledge that the manuscript does not yet provide quantitative evaluation of these mechanisms under realistic contention and loss rates. We will therefore extend the simulation section with new results that measure state-divergence probability, recovery latency, and fallback success rates across varying packet-loss and channel-contention conditions, thereby directly supporting the scalability claims. revision: yes

Circularity Check

0 steps flagged

No circularity: framework extends external ETSI standards with independent POC and simulations

full rationale

The paper introduces RAS/RMCS services and messages as extensions of ETSI Cooperative Awareness and Maneuver Coordination standards. The finite-state coordination model is described as formally specified and governs the POC demonstration, but no equations, self-citations, or fitted parameters are shown reducing the central claims (decentralized coordination, VRU integration, channel load reduction) to the inputs by construction. Simulations evaluate clustering independently. This is a standards-aligned proposal with external benchmarks; no load-bearing step collapses to self-definition or prior author work.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 2 invented entities

The central claim rests on the assumption that extending ETSI services with robot roles and finite-state models will deliver the stated coordination benefits; no free parameters are explicitly fitted in the abstract.

axioms (1)
  • domain assumption Finite-state coordination model governs deterministic robot behavior
    Invoked for the road-crossing proof of concept
invented entities (2)
  • Robot Awareness Service (RAS) no independent evidence
    purpose: Role-aware, task-oriented awareness including non-V2X VRUs
    New facility-layer service introduced in the framework
  • Robot Maneuver Coordination Service (RMCS) no independent evidence
    purpose: Event-driven low-latency coordination under established roles
    New facility-layer service introduced in the framework

pith-pipeline@v0.9.0 · 5533 in / 1171 out tokens · 44294 ms · 2026-05-08T08:36:13.595091+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

23 extracted references · 3 canonical work pages · 1 internal anchor

  1. [1]

    Understanding the interaction between delivery robots and other road and sidewalk users: A study of user-generated online videos,

    X. Yu, M. Hoggenm ¨uller, T. T. M. Tran, Y . Wang, and M. Tomitsch, “Understanding the interaction between delivery robots and other road and sidewalk users: A study of user-generated online videos,”ACM Transactions on Human-Robot Interaction, vol. 13, no. 4, 2024

    2024

  2. [2]

    Integrating multi-stakeholder communication into autonomous vehicle trolley problem,

    S. R. Milford, V . Laxton, and A. Vinel, “Integrating multi-stakeholder communication into autonomous vehicle trolley problem,” in2024 20th International Conference on Wireless and Mobile Computing, Network- ing and Communications (WiMob), 2024, pp. 68–73

    2024

  3. [3]

    Autonomous vehicles as social agents: Vehicle to pedestrian communication from v2x, ehmi and hri perspectives,

    M. Bied, B. Bruno, and A. Vinel, “Autonomous vehicles as social agents: Vehicle to pedestrian communication from v2x, ehmi and hri perspectives,” in2024 20th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2024, pp. 86–91

    2024

  4. [4]

    A bionic arm mechanism design and kinematic analysis of the humanoid traffic police,

    L. Zhao, L. Gong, X. Li, C. Yang, Z. Chen, Y . Huang, and C. Liu, “A bionic arm mechanism design and kinematic analysis of the humanoid traffic police,” in2019 IEEE 9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2019, pp. 1606–1611

    2019

  5. [5]

    Controlling traffic with humanoid social robot,

    F. Ghaffar, “Controlling traffic with humanoid social robot,” 2022. [Online]. Available: https://arxiv.org/abs/2204.04240

    work page arXiv 2022

  6. [6]

    Mika assistive humanoid robot for metro passengers,

    J. Ben, B. Varghese, and M. C, “Mika assistive humanoid robot for metro passengers,” inInternational Conference on Social Robotics. Springer, 2024, pp. 186–193

    2024

  7. [7]

    ROBOPOL: Social Robotics Meets Vehicular Communications for Cooperative Automated Driving

    J. P. Arockiasamy, A. Comeca, V . Yang, M. Bied, M. Schrapel, A. Rolich, B. Bruno, M. Schwammberger, D. Fiems, and A. Vinel, “Robopol: Social robotics meets vehicular communications for cooperative automated driving,” 2026. [Online]. Available: https://arxiv.org/abs/2512.24129

    work page internal anchor Pith review Pith/arXiv arXiv 2026

  8. [8]

    Robots for safer pedestrian crossing on two- lane roads,

    A. L. Flores Comeca, N. Masarykova, M. Halinkovic, M. Galinski, P. Laskov, and A. Vinel, “Robots for safer pedestrian crossing on two- lane roads,” in2025 IEEE IAVVC – International Automated Vehicle Validation Conference, 2025, pp. 1–6

    2025

  9. [9]

    TS 103 900 V2.1.1, Nov

    ETSI,Intelligent Transport Systems (ITS); Vehicular Communications; Facilities Layer; Cooperative Awareness (CA) service including Coop- erative Awareness Message (CAM) Release 2, Std. TS 103 900 V2.1.1, Nov. 2023

    2023

  10. [10]

    Intelligent transport systems (its); vulnerable road users (vru) awareness; part 3: Specification of vru awareness basic service; release 2,

    ETSI, “Intelligent transport systems (its); vulnerable road users (vru) awareness; part 3: Specification of vru awareness basic service; release 2,” no. TS 103 300-3 V2.2.1 (2023-02)

    2023

  11. [11]

    TS 103 324 V2.1.1, Jun

    ETSI,Intelligent Transport Systems (ITS); Vehicular Communica- tions; Basic Set of Applications; Collective Perception Service; Re- lease 2, European Telecommunications Standards Institute (ETSI) Std. TS 103 324 V2.1.1, Jun. 2023

    2023

  12. [12]

    Intelligent transport systems (its); vehicular communications; informative report for the manoeuvre coordination service (mcs),

    ETSI, “Intelligent transport systems (its); vehicular communications; informative report for the manoeuvre coordination service (mcs),” no. TR 103 578 V2.1.1 (2024-04)

    2024

  13. [13]

    A critical review of communi- cations in multi-robot systems,

    J. Gielis, A. Shankar, and A. Prorok, “A critical review of communi- cations in multi-robot systems,”Current robotics reports, vol. 3, no. 4, pp. 213–225, 2022

    2022

  14. [14]

    Cooperative perception for 3d object detection in driving scenarios using infrastruc- ture sensors,

    E. Arnold, M. Dianati, R. De Temple, and S. Fallah, “Cooperative perception for 3d object detection in driving scenarios using infrastruc- ture sensors,”IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 3, pp. 1852–1864, 2020

    2020

  15. [15]

    Context-aware content selection and message generation for collective perception services,

    A. Chtourou, P. Merdrignac, and O. Shagdar, “Context-aware content selection and message generation for collective perception services,” Electronics, vol. 10, no. 20, p. 2509, 2021

    2021

  16. [16]

    Non-negotiated implicit etsi vam clustering,

    F. Valle, D. Bleckert, L. Frisk, O. A. Molina, E. Haller, and A. Vinel, “Non-negotiated implicit etsi vam clustering,”arXiv preprint arXiv:2502.10617, 2025

    work page arXiv 2025

  17. [17]

    Infrastructure support for cooperative maneuvers in connected and automated driving,

    A. Correa, R. Alms, J. Gozalvez, M. Sepulcre, M. Rondinone, R. Blokpoel, L. L ¨ucken, and G. Thandavarayan, “Infrastructure support for cooperative maneuvers in connected and automated driving,” in2019 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2019, pp. 20–25

    2019

  18. [18]

    A framework of use cases, scenarios, and metrics for evaluation of v2x maneuver coordination,

    D. Maksimovski, C. Facchi, and A. Festag, “A framework of use cases, scenarios, and metrics for evaluation of v2x maneuver coordination,” in 2024 IEEE Vehicular Networking Conference (VNC). IEEE, 2024, pp. 1–8

    2024

  19. [19]

    (2025) Sumo: Simulation of urban mobility

    Eclipse SUMO Team. (2025) Sumo: Simulation of urban mobility. [Online; accessed 3-Nov-2025]. [Online]. Available: http://sourceforge.net/apps/mediawiki/sumo

    2025

  20. [20]

    Artery: Extending veins for vanet applications,

    R. Riebl, H.-J. G ¨unther, C. Facchi, and L. Wolf, “Artery: Extending veins for vanet applications,” in2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). IEEE, 2015, pp. 450–456

    2015

  21. [21]

    Pedestrian detection with lidar technology in smart-city deployments–challenges and recommen- dations,

    P. Torres, H. Marques, and P. Marques, “Pedestrian detection with lidar technology in smart-city deployments–challenges and recommen- dations,”Computers, vol. 12, no. 3, p. 65, 2023

    2023

  22. [22]

    Etsi tr 103 439 v2. 1.1-intelligent transport systems (its); multi- channel operation study; release 2,

    T. Etsi, “Etsi tr 103 439 v2. 1.1-intelligent transport systems (its); multi- channel operation study; release 2,”ETSI, Standard, 2021

    2021

  23. [23]

    Poster: Preliminary study - people’s opinion on social robots for traffic orchestration,

    M. Bied, M. Schrapel, and A. Vinel, “Poster: Preliminary study - people’s opinion on social robots for traffic orchestration,” in2025 IEEE Vehicular Networking Conference (VNC), 2025, pp. 1–2

    2025