Future planetary exploration missions demand high-performance, fault-tolerant computing to enable autonomous Guidance, Navigation, and Control (GNC) and Lander Vision System (LVS) operations during Entry, Descent, and Landing (EDL). This paper evaluates the deployment of GNC and LVS algorithms on next-generation multi-core processors--HPSC, Snapdragon VOXL2, and AMD Xilinx Versal--demonstrating up to 15x speedup for LVS image processing and over 250x speedup for Guidance for Fuel-Optimal Large Divert (GFOLD) trajectory optimization compared to legacy spaceflight hardware. To ensure computational reliability, we present ARBITER (Asynchronous Redundant Behavior Inspection for Trusted Execution and Recovery), a Multi-Core Voting (MV) mechanism that performs real-time fault detection and correction across redundant cores. ARBITER is validated in both static optimization tasks (GFOLD) and dynamic closed-loop control (Attitude Control System). A fault injection study further identifies the gradient computation stage in GFOLD as the most sensitive to bit-level errors, motivating selective protection strategies and vector-based output arbitration. This work establishes a scalable and energy-efficient architecture for future missions, including Mars Sample Return, Enceladus Orbilander, and Ceres Sample Return, where onboard autonomy, low latency, and fault resilience are critical.

翻译：未来的行星探测任务需要高性能、容错的计算能力，以实现在进入、下降与着陆（EDL）阶段自主运行制导、导航与控制（GNC）及着陆视觉系统（LVS）。本文评估了在新一代多核处理器——HPSC、Snapdragon VOXL2和AMD Xilinx Versal——上部署GNC与LVS算法的性能，结果显示LVS图像处理速度提升高达15倍，而燃料最优大幅机动制导（GFOLD）轨迹优化相比传统航天硬件加速超过250倍。为确保计算可靠性，我们提出了ARBITER（异步冗余行为检查可信执行与恢复机制），这是一种多核投票（MV）机制，可在冗余核心间执行实时故障检测与校正。ARBITER在静态优化任务（GFOLD）和动态闭环控制（姿态控制系统）中均得到验证。故障注入研究进一步识别出GFOLD中的梯度计算阶段对位级错误最为敏感，从而推动了选择性保护策略和基于向量的输出仲裁方法。本研究为未来任务——包括火星样本返回、土卫二轨道着陆器及谷神星样本返回——建立了一种可扩展且高能效的架构，其中机载自主性、低延迟和容错能力至关重要。