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Real-time, propellant-optimized spacecraft motion planning under Clohessy-Wiltshire-Hill dynamics

机译:Clohessy-Wiltshire-Hill Dynamics下的实时,推进剂优化的航天器运动计划

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This paper presents a sampling-based motion planning algorithm for real-time, propellant-optimized autonomous spacecraft trajectory generation in near-circular orbits. Specifically, this paper leverages recent algorithmic advances in the field of robot motion planning to the problem of impulsively-actuated, propellant-optimized rendezvous and proximity operations under the Clohessy-Wiltshire-Hill (CWH) dynamics model. The approach calls upon a modified version of the Fast Marching Tree (FMT???) algorithm to grow a set of feasible and actively-safe trajectories over a deterministic, low-dispersion set of sample points covering the free state space. Key features of the proposed algorithm include: (i) theoretical guarantees of trajectory safety and performance, (ii) real-time implementability, and (iii) generality, in the sense that a large class of constraints can be handled directly. As a result, the proposed algorithm offers the potential for widespread application, ranging from on-orbit satellite servicing to orbital debris removal and autonomous inspection missions.
机译:本文介绍了一种基于采样的运动规划算法,用于实时,推进剂优化的自主航天器轨迹轨迹轨迹轨迹轨迹。具体而言,本文利用了机器人运动领域的最近算法的进步,对Clohessy-Wiltshire-Hill(CWH)动力学模型下的冲动致动,推进剂优化的Rendezvous和接近操作的问题。该方法呼叫在快速行进树(FMT ???)算法的修改版本上,通过确定覆盖自由状态空间的确定性,低分散的样本点来生长一组可行和主动安全的轨迹。所提出的算法的关键特征包括:(i)轨迹安全性和性能的理论保证,(ii)实时可实现性,(iii)一般性,在可以直接处理大类约束的意义上。因此,该算法提供了广泛应用的潜力,从轨道卫星用于轨道碎片去除和自主检查任务的轨道卫星。

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