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arxiv: 1906.10945 · v1 · pith:AS6XKKPFnew · submitted 2019-06-26 · 📡 eess.SY · cs.SY

Sliding Mode Control Techniques and Artificial Potential Field for Dynamic Collision Avoidance in Rendezvous Maneuvers

Mauro Mancini , Nicoletta Bloise , Elisa Capello , Elisabetta Punta This is my paper

Pith reviewed 2026-05-25 15:53 UTC · model grok-4.3

classification 📡 eess.SY cs.SY
keywords rendezvous maneuverscollision avoidancesliding mode controlartificial potential fieldspacecraft guidancedynamic obstaclesproximity operations
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The pith

Combining artificial potential fields with sliding mode control guarantees safe spacecraft rendezvous paths around dynamic obstacles.

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

The paper develops an integrated guidance and control approach for autonomous spacecraft rendezvous that must avoid obstacles. An artificial potential field generates repulsive forces from obstacles and attractive forces toward the target to produce a reference trajectory. Sliding mode controllers, in both component-wise and simplex-based forms, track this reference for position and attitude while rejecting disturbances. Six-degree-of-freedom orbital simulations demonstrate that the closed-loop system maintains safe separation from both static and moving obstacles. This matters because real-time onboard computation must remain low for practical space operations.

Core claim

The proposed closed-loop system is able to guarantee a safe path in a real environment, as well as robustness with respect to external disturbances and dynamic obstacles. The guidance strategy exploits a suitably designed Artificial Potential Field while the controller relies on Sliding Mode Control for both position and attitude tracking. The integrated strategy is validated by extensive simulations performed with a six degree-of-freedom orbital simulator and appears suitable for real-time control with minimal on-board computational effort.

What carries the argument

Artificial Potential Field guidance that produces reference trajectories through attractive and repulsive potentials, paired with first-order Sliding Mode Control (component-wise and simplex-based) that enforces tracking of position and attitude commands.

If this is right

  • The closed-loop system maintains safe separation from dynamic obstacles throughout the maneuver.
  • Robustness to external disturbances holds across the tested orbital conditions.
  • Fuel consumption and total control effort remain quantifiable at different closed-loop update rates.
  • The approach operates with low enough computational load to support real-time onboard execution.

Where Pith is reading between the lines

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

  • The same potential-field-plus-sliding-mode structure could be tested for multi-spacecraft formation flying or debris avoidance.
  • Adding explicit fuel-optimal replanning on top of the potential field might further reduce propellant use.
  • Communication latency between vehicles would require checking whether the local potential field still prevents collisions.

Load-bearing premise

The six-degree-of-freedom orbital simulator used for validation accurately represents the dynamics, disturbances, and obstacle behaviors encountered during actual spacecraft rendezvous maneuvers.

What would settle it

A physical flight test or hardware-in-the-loop experiment in which the spacecraft collides with a dynamic obstacle or loses separation under recorded disturbance levels would falsify the safety guarantee.

Figures

Figures reproduced from arXiv: 1906.10945 by Elisabetta Punta, Elisa Capello, Mauro Mancini, Nicoletta Bloise.

Figure 1
Figure 1. Figure 1: Vectors for defining the new repulsive potential [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Complete trajectory in a V-bar and R-bar plane. Upper part: [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 4
Figure 4. Figure 4: Sliding variables of the position tracking for the cone approach [PITH_FULL_IMAGE:figures/full_fig_p006_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Air density in function of the altitude • The aerodynamic drag is due to the residual air particles in space environment. Actually, [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
read the original abstract

The paper considers autonomous rendezvous maneuver and proximity operations of two spacecraft in presence of obstacles. A strategy that combines guidance and control algorithms is analyzed. The proposed closed-loop system is able to guarantee a safe path in a real environment, as well as robustness with respect to external disturbances and dynamic obstacles. The guidance strategy exploits a suitably designed Artificial Potential Field (APF), while the controller relies on Sliding Mode Control (SMC), for both position and attitude tracking of the spacecraft. As for the position control, two different first order SMC methods are considered, namely the component-wise and the simplex-based control techniques. The proposed integrated guidance and control strategy is validated by extensive simulations performed with a six degree-of-freedom (DOF) orbital simulator and appears suitable for real-time control with minimal on-board computational effort. Fuel consumption and control effort are evaluated, including different update frequencies of the closed-loop software.

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 / 1 minor

Summary. The paper proposes an integrated guidance-control strategy for autonomous spacecraft rendezvous and proximity operations in the presence of dynamic obstacles. Guidance uses a suitably designed Artificial Potential Field (APF), while control employs first-order Sliding Mode Control (SMC) for both position (component-wise and simplex-based variants) and attitude tracking. The central claim is that the closed-loop system guarantees a safe path in a real environment and provides robustness to external disturbances and dynamic obstacles. Validation consists of extensive 6DOF orbital simulations that evaluate fuel consumption and control effort across different closed-loop update frequencies, with the method asserted to be suitable for real-time onboard use.

Significance. If the robustness claims hold beyond simulation, the work would demonstrate a practical, low-computational-effort combination of established APF and SMC techniques for collision avoidance during rendezvous, with explicit performance metrics (fuel, effort) across update rates. The extensive 6DOF simulation campaign including disturbance and obstacle scenarios is a positive aspect of the validation approach.

major comments (2)
  1. [Abstract] Abstract: the claim that the proposed closed-loop system is 'able to guarantee a safe path in a real environment, as well as robustness with respect to external disturbances and dynamic obstacles' is load-bearing for the paper's contribution but rests solely on numerical 6DOF simulations; no Lyapunov-style stability analysis, invariance arguments for the APF, or bounded-disturbance rejection proofs are referenced for the combined guidance-control loop.
  2. [Abstract] Validation description (abstract and implied results section): the abstract provides no quantitative error bounds, explicit disturbance models, or comparison baselines against other guidance-control methods, so the robustness and real-environment suitability assertions are only partially supported by the simulation campaign despite its breadth.
minor comments (1)
  1. [Abstract] The abstract could more precisely state the quantitative metrics (e.g., specific fuel-consumption values or effort norms) obtained from the simulations rather than only describing that they 'are evaluated'.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments. We address the major points below, focusing on moderating the abstract claims to better reflect the simulation-based nature of the validation while preserving the paper's emphasis on practical integration and performance evaluation.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the claim that the proposed closed-loop system is 'able to guarantee a safe path in a real environment, as well as robustness with respect to external disturbances and dynamic obstacles' is load-bearing for the paper's contribution but rests solely on numerical 6DOF simulations; no Lyapunov-style stability analysis, invariance arguments for the APF, or bounded-disturbance rejection proofs are referenced for the combined guidance-control loop.

    Authors: The manuscript presents the integration of APF guidance with two SMC variants and validates the closed-loop behavior exclusively through extensive 6DOF orbital simulations that incorporate external disturbances and dynamic obstacles. No formal Lyapunov analysis or invariance proofs for the combined system are included, as the contribution centers on demonstrating practical performance and real-time feasibility rather than theoretical guarantees. We will revise the abstract to replace 'guarantee' with 'demonstrate through simulation the ability to maintain' a safe path under the tested conditions. revision: yes

  2. Referee: [Abstract] Validation description (abstract and implied results section): the abstract provides no quantitative error bounds, explicit disturbance models, or comparison baselines against other guidance-control methods, so the robustness and real-environment suitability assertions are only partially supported by the simulation campaign despite its breadth.

    Authors: The abstract is intentionally concise and summarizes the validation approach without specific quantitative details or baselines. The body of the paper reports fuel consumption, control effort, and results across multiple closed-loop update frequencies, with disturbance and obstacle scenarios included in the 6DOF simulator. We will partially revise the abstract to briefly reference the evaluated metrics (fuel use and update rates) and the inclusion of disturbance models, without adding new comparisons. revision: partial

Circularity Check

0 steps flagged

No circularity detected; methods drawn from external literature and validated externally.

full rationale

The paper applies standard Artificial Potential Field guidance and Sliding Mode Control (component-wise and simplex-based) drawn from prior literature to the rendezvous problem. Validation occurs via independent 6DOF orbital simulator runs evaluating fuel, effort, and obstacle avoidance under disturbances. No equations reduce a claimed result to a fitted parameter defined by the authors, no uniqueness theorems are imported via self-citation, and no ansatz or renaming loops appear. The derivation chain is self-contained against external benchmarks with no load-bearing self-referential steps.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The work relies on standard assumptions from sliding mode control theory and artificial potential field methods without introducing new free parameters, axioms beyond domain conventions, or invented entities.

axioms (2)
  • domain assumption Sliding mode control can enforce finite-time convergence to a sliding surface despite bounded disturbances in spacecraft dynamics.
    Invoked implicitly when claiming robustness of the SMC position and attitude loops.
  • domain assumption Artificial potential fields produce collision-free paths when repulsive potentials are suitably tuned around obstacles.
    Central to the guidance strategy described in the abstract.

pith-pipeline@v0.9.0 · 5693 in / 1295 out tokens · 25091 ms · 2026-05-25T15:53:54.251104+00:00 · methodology

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Reference graph

Works this paper leans on

23 extracted references · 23 canonical work pages

  1. [1]

    Fehse, Automated rendezvous and docking of spacecraft

    W. Fehse, Automated rendezvous and docking of spacecraft . Cambridge University Press, 2003

    work page 2003

  2. [2]

    Survey of orbital dynamics and control of space rendezvous,

    Y . Luo, J. Zhang, and G. Tang, “Survey of orbital dynamics and control of space rendezvous,” Chinese Journal of Aeronautics , vol. 27, no. 1, pp. 1–11, 2014

    work page 2014

  3. [3]

    Khatib, The Potential Field Approach And Operational Space F or- mulation In Robot Control

    O. Khatib, The Potential Field Approach And Operational Space F or- mulation In Robot Control . Springer US, 1986

    work page 1986

  4. [4]

    V . I. Utkin, Sliding modes in optimization and control problems . Springer Verlag, New York, 1992

    work page 1992

  5. [5]

    Shtessel, C

    Y . Shtessel, C. Edwards, L. Fridman, and A. Levant, Sliding mode control and observation. Springer Science+Business Media, New York, 2014

    work page 2014

  6. [6]

    Vector method of design of sliding motion and simplex algorithms,

    S. V . Bajda and D. B. Izosimov, “Vector method of design of sliding motion and simplex algorithms,” Automat. Remote Control , vol. 46, pp. 830–837, 1985

    work page 1985

  7. [7]

    A control vector simplex approach to variable structure control,

    G. Bartolini, A. Ferrara, V . Utkin, and T. Zolezzi, “A control vector simplex approach to variable structure control,” International Journal of Robust and Nonlinear Control , vol. 7, no. 04, pp. 321–335, 1997

    work page 1997

  8. [8]

    Simplex methods for nonlin- ear uncertain sliding-mode control,

    G. Bartolini, E. Punta, and T. Zolezzi, “Simplex methods for nonlin- ear uncertain sliding-mode control,” IEEE Transactions on Automatic Control, vol. 49, no. 07, pp. 922 – 933, 2004

    work page 2004

  9. [9]

    Multi-input sliding mode control of nonlinear uncertain non-affine systems with mono-directional actuation,

    G. Bartolini and E. Punta, “Multi-input sliding mode control of nonlinear uncertain non-affine systems with mono-directional actuation,” IEEE Transactions on Automatic Control , vol. 60, no. 2, pp. 393–403, 2015

    work page 2015

  10. [10]

    Simplex based sliding mode control of an underwater gripper,

    G. Bartolini, M. Coccoli, and E. Punta, “Simplex based sliding mode control of an underwater gripper,” Journal of Dynamic Systems, Mea- surement, and Control , vol. 122, no. 4, pp. 604–610, 2000

    work page 2000

  11. [11]

    Simplex sliding mode control strategies for spacecraft rendezvous maneuvers,

    E. Capello, E. Punta, and G. Bartolini, “Simplex sliding mode control strategies for spacecraft rendezvous maneuvers,” IF AC-PapersOnLine, vol. 50, no. 1, pp. 8496–8501, 2017

    work page 2017

  12. [12]

    Sliding mode control for gradient tracking and robot navigation using artificial potential fields,

    J. Guldner and V . I. Utkin, “Sliding mode control for gradient tracking and robot navigation using artificial potential fields,”IEEE Transactions on Robotics and Automation , vol. 11, no. 2, pp. 247–254, 1995

    work page 1995

  13. [13]

    Experiments on autonomous spacecraft rendezvous and docking using an adaptive artificial potential field approach,

    R. I. Zappulla, H. Park, J. Virgili-Llop, and M. Romano, “Experiments on autonomous spacecraft rendezvous and docking using an adaptive artificial potential field approach,” 2016

    work page 2016

  14. [14]

    Sliding- mode control strategies for rendezvous and docking maneuvers,

    E. Capello, E. Punta, F. Dabbene, G. Guglieri, and R. Tempo, “Sliding- mode control strategies for rendezvous and docking maneuvers,” Journal of Guidance, Control, and Dynamics , vol. 40, no. 6, pp. 1481–1487, 2017

    work page 2017

  15. [15]

    Sliding order and sliding accuracy in sliding mode control,

    A. Levant, “Sliding order and sliding accuracy in sliding mode control,” International journal of control , vol. 58, no. 6, pp. 1247–1263, 1993

    work page 1993

  16. [16]

    Obstacle avoidance with potential field applied to a rendezvous maneuver,

    N. Bloise, E. Capello, M. Dentis, and E. Punta, “Obstacle avoidance with potential field applied to a rendezvous maneuver,”Applied Sciences, vol. 7, no. 10, p. 1042, 2017

    work page 2017

  17. [17]

    F. L. Markley and J. L. Crassidis, Fundamentals of spacecraft attitude determination and control . Springer, 2014

    work page 2014

  18. [18]

    M. J. Sidi, Spacecraft dynamics and control: a practical engineering approach. Cambridge university press, 1997

    work page 1997

  19. [19]

    Motion-based mass-and thruster- property identification for thruster-controlled spacecraft,

    E. Wilson, D. Sutter, and R. Mah, “Motion-based mass-and thruster- property identification for thruster-controlled spacecraft,” inProceedings of the 2005 AIAA Infotech@ Aerospace Conference , 2005

    work page 2005

  20. [20]

    Motion-based thruster fault detection and isolation,

    ——, “Motion-based thruster fault detection and isolation,” in Proceed- ings of the 2005 AIAA Infotech@ Aerospace Conference , 2005

    work page 2005

  21. [21]

    Dynamic motion planning for mobile robots using potential field method,

    S. S. Ge and Y . J. Cui, “Dynamic motion planning for mobile robots using potential field method,” Autonomous robots , vol. 13, no. 3, pp. 207–222, 2002

    work page 2002

  22. [22]

    Simplex sliding mode control of multi-input systems with chattering reduction and mono-directional actuators,

    G. Bartolini, E. Punta, and T. Zolezzi, “Simplex sliding mode control of multi-input systems with chattering reduction and mono-directional actuators,” Automatica, vol. 47, no. 11, pp. 2433–2437, 2011

    work page 2011

  23. [23]

    Modeling disturbances influencing an earth-orbiting satel- lite,

    P. Zag ´orski, “Modeling disturbances influencing an earth-orbiting satel- lite,” Pomiary Automatyka Robotyka , vol. 16, pp. 98–103, 2012

    work page 2012