Obstacle Avoidance with Potential Field Applied to a Rendezvous Maneuver

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.

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“…As in [16], the Chaser approaches the goal thanks to a paraboloid attractive artificial potential field defined as…”

Section: A Attractive Potential Fieldmentioning

confidence: 99%

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

Mancini

Bloise

Capello

et al. 2020

IEEE Control Syst. Lett.

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“…As discussed in details in [28], the advantage of the use of the artificial potential fields for a rendezvous maneuver is twofold: (i) an autonomous way for the desired path is designed with a low computational effort, and (ii) an online update of the path is guaranteed, in particular in the the presence of obstacles. The algorithm, here described, can be combined with a sliding mode control (SMC), including both position and attitude dynamics.…”

Section: Artificial Potential Fieldsmentioning

confidence: 99%

“Flyable” Guidance and Control Algorithms for Orbital Rendezvous Maneuver

Capello

Dabbene

Guglieri

et al. 2018

SICE Journal of Control, Measurement, and System Integration

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: Rendezvous orbital maneuvers are planned operations which intend to make two spacecraft meet, while avoiding collisions. Aspects such as trajectory safety and robustness, as well as obstacle avoidance, are fundamental for the mission success. The aim of this paper is to provide an overview of some recent algorithms for guidance and control systems, and also their combined exploitation, which can provide significant enhancements. This overview focuses on those algorithms that are characterized by key selected features: the discussed schemes guarantee low computational effort, low fuel consumption, and high safety and robustness. Different experimental setups, which can be used to evaluate the performance of the considered algorithms, are also taken into account and presented.

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“…Chen et al used the artificial potential field method to perform on-orbit assembly of four flexible spacecraft, and the proposed control strategy can protect the chaser spacecraft against collision before reaching the desired position [33]. Bloise designed the obstacle avoidance guidance algorithm by combining artificial potential field theory with sliding mode technology [34]. In terms of safety research on rendezvous and docking with noncooperative target, Zhang et al concentrated on obstacle avoidance using artificial potential field guidance [35].…”

Section: Introductionmentioning

confidence: 99%

Artificial Potential Function Safety and Obstacle Avoidance Guidance for Autonomous Rendezvous and Docking with Noncooperative Target

Liu

2019

Mathematical Problems in Engineering

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The problem of artificial potential function (APF) safety and obstacle avoidance guidance for autonomous rendezvous and docking of chaser spacecraft with noncooperative spacecraft is studied. The relative motion equation of the chaser and the target is established based on the line-of-sight coordinate system, the reference state is designed, and the corresponding state error is deduced. The attitude motion equation of the noncooperative target spacecraft in space is established. The safety and obstacle avoidance guidance problem of autonomous rendezvous and docking with noncooperative target is transformed into a path planning problem in a dynamic environment. The attractive potential function is designed according to the state error. In order to ensure that the chaser can safely approach the noncooperative target spacecraft, a safe corridor with ellipse cissoid is designed in the final approaching stage of autonomous rendezvous and docking. The obstacle is assumed to be a sphere with a certain radius to avoid its influence in the approach, and the obstacle potential function is designed based on the Gaussian function method. The total potential function of the system is designed according to the attractive potential function, the safe potential function, and the obstacle potential function. The total potential function of the system is modified to ensure that the reference state is the minimum of the total potential function of the system. The stability of the system is proven according to the Lyapunov stability principle, and the conditions for satisfying the monotonic decrease in the total potential function of the system are deduced. Finally, the effectiveness of the proposed method is verified by three sets of numerical simulations.

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Obstacle Avoidance with Potential Field Applied to a Rendezvous Maneuver

Cited by 17 publications

References 20 publications

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

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

“Flyable” Guidance and Control Algorithms for Orbital Rendezvous Maneuver

Artificial Potential Function Safety and Obstacle Avoidance Guidance for Autonomous Rendezvous and Docking with Noncooperative Target

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