Docking of Autonomous Vehicles with a Stationary Docking Station in 3D Space

Hemendra Arya; Ram Milan Kumar Verma; Shashi Ranjan Kumar

arxiv: 2607.02478 · v1 · pith:4GCIVNZDnew · submitted 2026-07-02 · 📡 eess.SY · cs.SY

Docking of Autonomous Vehicles with a Stationary Docking Station in 3D Space

Ram Milan Kumar Verma , Shashi Ranjan Kumar , Hemendra Arya This is my paper

Pith reviewed 2026-07-03 07:19 UTC · model grok-4.3

classification 📡 eess.SY cs.SY

keywords autonomous dockingsliding mode controlline-of-sight kinematicsfinite-time convergence3D vehicle guidancerange-based control

0 comments

The pith

A finite-time sliding mode strategy using range and line-of-sight kinematics achieves safe autonomous docking in 3D space.

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

This paper develops a control method for autonomous vehicles to dock with a fixed station in three-dimensional environments. The method ensures the vehicle reaches a specific orientation relative to the station while slowing to nearly zero speed to avoid collision. It draws on guidance principles to design a sliding mode controller that converges in finite time. The design uses only measurements of distance and line-of-sight angles between the vehicle and station. This matters because docking is safety-critical in applications like aerial, marine, and space vehicles where precise alignment is needed.

Core claim

The paper presents a finite-time sliding mode-based strategy that uses range and line-of-sight kinematics relations to steer the vehicle to the desired orientation for docking and reduce its speed to near-zero.

What carries the argument

finite-time sliding mode control law derived from range and line-of-sight kinematics relations

If this is right

The vehicle achieves the required orientation and terminal speed from a range of initial positions and attitudes.
The controller relies solely on range and line-of-sight information rather than full dynamic models.
MATLAB simulations confirm successful docking across varied initial locations and orientations of both vehicle and station.

Where Pith is reading between the lines

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

Practical deployment would need additional compensation for disturbances and actuator constraints omitted from the kinematic model.
The same kinematic sliding-mode structure could be adapted for docking with a moving station by updating the reference kinematics.
The finite-time property may permit explicit bounds on docking duration once the gain parameters are fixed.

Load-bearing premise

The range and line-of-sight kinematics relations describing the motion of the vehicle with respect to the stationary docking station are sufficient to design a control law that achieves safe docking.

What would settle it

A simulation in which the vehicle under the proposed control law fails to reach the desired orientation or near-zero speed for at least one set of initial conditions satisfying the kinematic model.

Figures

Figures reproduced from arXiv: 2607.02478 by Hemendra Arya, Ram Milan Kumar Verma, Shashi Ranjan Kumar.

**Figure 2.** Figure 2: Approach angle of the vehicle to the docking station. Problem 1: Consider the engagement scenario as represented in [PITH_FULL_IMAGE:figures/full_fig_p002_2.png] view at source ↗

**Figure 1.** Figure 1: shows the representation of the geometric engagement [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗

**Figure 3.** Figure 3: Demonstration of docking for various initial locations of the vehicle while fixed docking station. 0 15 5 10 10 Z m ( ) 10 15 Y (m) 5 X (m) 20 0 0 -5 -10 D1 D2 D3 (a) Path of the vehicle. 0 10 20 30 40 VU ( m / s ) 0 2 4 D1 D2 D3 0 10 20 30 40 R ( m ) 0 10 20 Time (s) 0 10 20 30 40 _R ( m / s ) -2 -1 0 (b) Speed, range and closing rate. a 0 10 20 30 40 U x ( m / s 2 ) 0 1 2 3 D1 D2 D3 a 0 10 20 30 40 U y (… view at source ↗

**Figure 4.** Figure 4: Demonstration of docking for various locations of the docking station while fixed vehicle initial location. 10 X (m) 0 5 10 2 Z 4 ( m )6 5 Y (m) 0 8 10 0 App1 App2 App3 (a) Path of the vehicle. 0 10 20 30 40 VU ( m / s ) 0 1 2 App1 App2 App3 0 10 20 30 40 R ( m ) 0 10 20 Time (s) 0 10 20 30 40 _R ( m / s ) -1 -0.5 0 (b) Speed, range and closing rate. a 0 10 20 30 40 U x ( m / s 2 ) 0 0.5 1 App1 App2 App3 a… view at source ↗

**Figure 5.** Figure 5: Demonstration of docking for various approach angles with the same docking station location and initial vehicle location. [3] D.-j. Li, Y.-h. Chen, J.-g. Shi, and C.-j. Yang, “Autonomous underwater vehicle docking system for cabled ocean observatory network,” Ocean Engineering, vol. 109, pp. 127–134, 2015. [4] Y. Li, Y. Jiang, J. Cao, B. Wang, and Y. Li, “AUV docking experiments based on vision positioning… view at source ↗

read the original abstract

In this letter, we present a strategy for autonomous docking of autonomous vehicles in three-dimensional space. Docking is a safety-critical task and requires expert piloting skills. Vehicles with autonomous docking capabilities are highly desirable in various applications, such as marine vehicle docking, aerial vehicle docking, spacecraft docking, and landing. To dock autonomously with the docking station, the vehicle must align itself to a specific desired orientation relative to the docking station and also reduce speed as it approaches. The vehicle achieves near-zero speed to dock successfully and safely without colliding with the docking station. Inspired by the philosophies from the guidance literature, we present a finite-time sliding mode-based strategy to achieve the same. The range and line-of-sight kinematics relations describing the motion of the vehicle with respect to the stationary docking station are used to steer the vehicle to achieve the desired orientation for docking. This docking strategy is validated in MATLAB\textsuperscript{\textregistered} simulations for various initial locations and orientations of both the vehicle and the docking station.

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.

Desk Editor's Note private letter to a colleague

Kinematics-only finite-time sliding mode for 3D docking works in ideal simulations but skips vehicle dynamics, disturbances, and actuator limits.

read the letter

The paper gives a sliding-mode law built from range and line-of-sight rate equations to steer an autonomous vehicle to a fixed docking station in 3D while aligning orientation and driving speed to near zero. It draws on standard guidance relations and shows MATLAB runs that reach the target from scattered initial positions and attitudes.

The work is straightforward in its construction and the simulations cover a useful range of starting conditions. The finite-time convergence claim follows directly from the chosen sliding surface on the kinematic manifold.

The central limitation is that the plant is treated as pure kinematics. No 6-DOF rigid-body equations, inertia, thrust mapping, saturation, or disturbance terms enter the derivation or the validation. The finite-time result therefore holds only under the assumption that commanded velocities are realized instantly and perfectly. That assumption is common in early guidance papers but leaves open whether the closed-loop behavior survives on an actual vehicle.

The paper is aimed at control engineers who need a concrete docking example for marine, aerial, or space vehicles. Readers already comfortable with sliding-mode guidance will see an incremental application rather than a new theoretical step. The citation pattern stays within established LOS and sliding-mode references, which is consistent with the scope.

It is coherent on its own terms and shows clear thinking about the kinematic problem. A serious editor could reasonably send it to referees, provided the authors are asked to address dynamic validation and robustness. I would not cite it in my own work unless a later version adds those checks.

Referee Report

2 major / 0 minor

Summary. The paper proposes a finite-time sliding-mode control strategy for autonomous 3D docking of vehicles with a stationary station. The approach uses range and line-of-sight (LOS) kinematics to generate commands that align the vehicle to a desired orientation while driving relative speed to near zero; the law is derived from standard guidance relations and validated only via MATLAB simulations across varied initial conditions.

Significance. If the kinematic convergence result transfers to a closed-loop dynamic system, the method would supply a simple, parameter-light guidance law for safety-critical docking tasks in marine, aerial, and spacecraft applications. The manuscript supplies no machine-checked proofs, reproducible code, or falsifiable dynamic predictions, so its contribution rests entirely on the simulation outcomes.

major comments (2)

[Abstract and kinematics-usage paragraph] Abstract and the paragraph on kinematics usage: the finite-time sliding-mode commands are derived directly from the range and LOS rate equations, treating these kinematic relations as the plant. No 6-DOF rigid-body equations, inertia matrix, thrust mapping, saturation limits, or disturbance model appear, so the proven convergence on the kinematic manifold does not automatically transfer to the physical vehicle.
[Simulation validation] Simulation validation section: all reported trials assume perfect velocity tracking with no sensor noise, external disturbances, or actuator dynamics. This leaves the central safety claim (near-zero speed docking without collision) supported only under idealized conditions that match the omitted dynamics.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the detailed and constructive feedback. Our response addresses each major comment in turn, clarifying the intended kinematic scope of the work while acknowledging its limitations.

read point-by-point responses

Referee: [Abstract and kinematics-usage paragraph] Abstract and the paragraph on kinematics usage: the finite-time sliding-mode commands are derived directly from the range and LOS rate equations, treating these kinematic relations as the plant. No 6-DOF rigid-body equations, inertia matrix, thrust mapping, saturation limits, or disturbance model appear, so the proven convergence on the kinematic manifold does not automatically transfer to the physical vehicle.

Authors: The manuscript intentionally develops and analyzes the guidance law at the kinematic level using range and line-of-sight relations, as is common in the guidance literature for deriving commands that can later be tracked by an inner-loop dynamic controller. Convergence is established for the kinematic system, and the approach assumes perfect command tracking by lower-level controllers (a standard cascaded structure). We agree that this does not automatically guarantee performance on a full 6-DOF vehicle with inertia, saturation, or disturbances. In revision we will explicitly state the kinematic scope in the abstract and introduction and add a brief note on the required inner-loop assumption. revision: partial
Referee: [Simulation validation] Simulation validation section: all reported trials assume perfect velocity tracking with no sensor noise, external disturbances, or actuator dynamics. This leaves the central safety claim (near-zero speed docking without collision) supported only under idealized conditions that match the omitted dynamics.

Authors: The simulations validate the kinematic law under ideal velocity tracking, which is the appropriate test for a guidance strategy before dynamic integration. We acknowledge that the safety claim (near-zero relative speed at docking) holds only under these idealized conditions and does not yet address noise or disturbances. In revision we will expand the discussion to highlight these assumptions and outline future dynamic validation steps, without altering the existing simulation results. revision: partial

Circularity Check

0 steps flagged

No circularity: derivation from standard range/LOS kinematics and sliding-mode guidance is independent

full rationale

The paper constructs its finite-time sliding-mode docking commands directly from the range and line-of-sight kinematic relations (abstract and kinematics-usage section), treating these as the plant model and citing external guidance literature for the underlying philosophy. No equation reduces by construction to a fitted parameter, self-referential quantity, or load-bearing self-citation chain; the central claim remains an independent mapping from the kinematic manifold to the control law. This is the most common honest finding for a kinematics-only guidance paper.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The approach rests on standard sliding mode control assumptions and kinematic models; no new free parameters, axioms, or invented entities are introduced beyond those implicit in the cited guidance literature.

axioms (2)

domain assumption Finite-time convergence properties of sliding mode control hold when applied to the range and line-of-sight kinematic model.
Invoked when stating the finite-time sliding mode strategy achieves the docking conditions.
domain assumption Range and line-of-sight kinematics accurately capture the relative motion needed for control design.
Stated directly in the abstract as the basis for steering the vehicle.

pith-pipeline@v0.9.1-grok · 5712 in / 1426 out tokens · 32970 ms · 2026-07-03T07:19:41.186823+00:00 · methodology

discussion (0)

Reference graph

Works this paper leans on

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T. Xie, Y . Li, Y . Jiang, S. Pang, and X. Xu, “Three-dimensional mobile docking control method of an underactuated autonomous underwater vehicle,”Ocean Engineering, vol. 265, p. 112634, 2022

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Autonomous underwater vehicle docking,

J. G. Bellingham, “Autonomous underwater vehicle docking,” in Springer Handbook of Ocean Engineering, ser. Springer Handbooks, M. R. Dhanak and N. I. Xiros, Eds. Springer, 2016, pp. 387–406

2016

[11] [11]

A USV-based automated launch and recovery system for AUVs,

E. I. Sarda and M. R. Dhanak, “A USV-based automated launch and recovery system for AUVs,”IEEE Journal of Oceanic Engineering, vol. 42, no. 1, pp. 37–55, 2017

2017

[12] [12]

Au- tonomous docking of hovering type AUV to seafloor charging station based on acoustic and visual sensing,

Y . Sato, T. Maki, K. Masuda, T. Matsuda, and T. Sakamaki, “Au- tonomous docking of hovering type AUV to seafloor charging station based on acoustic and visual sensing,” in2017 IEEE Underwater Technology (UT), 2017, pp. 1–6

2017

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S. R. Kumar and D. Ghose, “Three-dimensional impact angle guidance with coupled engagement dynamics,”Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 231, no. 4, pp. 621–641, 2017

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R. V . Nanavati, S. R. Kumar, and A. Maity, “Spatial nonlinear guidance strategies for target interception at pre-specified orientation,”Aerospace Science and Technology, vol. 114, p. 106735, 2021

2021

[15] [15]

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K. Majumder and S. R. Kumar, “Three-dimensional impact angle constrained nonlinear guidance with predefined convergence time,” Nonlinear Dynamics, vol. 112, no. 12, pp. 9983–10 008, 2024

2024

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Quaternion-based non-singular nonlinear impact angle guidance for three-dimensional engagements,

P. Surve, A. Maity, and S. R. Kumar, “Quaternion-based non-singular nonlinear impact angle guidance for three-dimensional engagements,” Aerospace Science and Technology, vol. 155, p. 109657, 2024

2024

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Autonomous docking of uncrewed surface vessel with stationary and moving ships,

R. M. K. Verma, S. R. Kumar, and H. Arya, “Autonomous docking of uncrewed surface vessel with stationary and moving ships,”Journal of Guidance, Control, and Dynamics, vol. 49, no. 6, pp. 1860–1869, 2026

2026