Arborist：面向快速高效运动规划的算法-硬件协同设计
Arborist: Algorithm-Hardware Co-Design for Fast and Efficient Motion Planning
- Arizona State University（亚利桑那州立大学）
- Rutgers University（罗格斯大学）
- Columbia University（哥伦比亚大学）
- Google（谷歌）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出Arborist，一种算法-硬件协同设计框架，通过多树并行与专用加速器架构，实现FMT*运动规划超过1000倍加速，并显著提升面积与能效。
AI中文摘要：
实时运动规划必须在资源受限平台上于严格的延迟和能量约束下执行。本文提出Arborist，一种算法-硬件协同设计框架，通过算法与架构的协同创新加速快速行进树（FMT*）运动规划。在算法层面，Arborist引入带全局竞争管理的安全多树扩展和跨树最优性检查，以暴露树间并行性，同时保持路径质量。在架构层面，我们提出的ArboristAccel集成了一个Arborist工具箱，为树间并行性提供硬件支持；一个KD树子系统，用于高吞吐近邻搜索；一个并行查询检索模块，通过平衡多存储体访问来缓解系统级内存带宽瓶颈；以及一个前瞻规划引擎，利用树内并行性，同时通过按序提交保持路径质量。ArboristAccel采用16 nm工艺综合，工作频率为500 MHz，在所有工作负载上相较于CPU实现超过1000倍加速，在2D-Maze上峰值达2800倍，相较于FMT* ASIC基线，几何平均加速8.8倍、面积效率提升4.6倍、能效提升3.1倍。相较于最先进的基于RRT*的MOPED加速器，在相当路径成本下，相应因子分别为8.6倍、1.0倍和1.8倍。据我们所知，ArboristAccel是首个专用于基于FMT*运动规划的硬件加速器。
英文摘要：
Real-time motion planning must execute under strict latency and energy constraints on resource-limited platforms. This paper presents Arborist, an algorithm-hardware co-design framework that accelerates Fast Marching Tree (FMT*) motion planning through synergistic algorithmic and architectural innovations. At the algorithm level, Arborist introduces safe multi-tree expansion with global competition management and cross-tree optimality checking to expose inter-tree parallelism while preserving path quality. At the architecture level, our proposed ArboristAccel integrates an Arborist Toolbox that provides hardware support for inter-tree parallelism; a KD-tree Subsystem for high-throughput near-neighbor search; a Parallel-Query Retrieval module that balances multi-bank memory accesses to alleviate system-level memory bandwidth bottlenecks; and a Look-ahead Planning Engine that exploits intra-tree parallelism while preserving path quality by in-order commit. Synthesized in 16 nm and operating at 500 MHz, ArboristAccel sustains more than 1000x speedup over CPU across all workloads, peaking at 2800x on 2D-Maze, and delivers geomean improvements of 8.8x speedup, 4.6x area efficiency, and 3.1x power efficiency over an FMT* ASIC baseline. The corresponding factors relative to a state-of-the-art RRT*-based MOPED accelerator are 8.6x, 1.0x, and 1.8x, at comparable path cost. To the best of our knowledge, ArboristAccel is the first dedicated hardware accelerator for FMT*-based motion planning.
