Perception still remains a challenging problem for autonomous navigation in unknown environment, especially for aerial vehicles. Most mapping algorithms for autonomous navigation are specifically designed for their very intended task, which hinders extended usage or cooperative task. In this paper, we propose a voxel mapping system that can build an adaptable map for multiple tasks. The system employs hash table-based map structure and manages each voxel with spatial and temporal priorities without explicit map boundary. We also introduce an efficient map-sharing feature with minimal bandwidth to enable multi-agent applications. We tested the system in real world and simulation environment by applying it for various tasks including local mapping, global mapping, cooperative multi-agent navigation, and high-speed navigation. Our system proved its capability to build customizable map with high resolution, wide coverage, and real-time performance regardless of sensor and environment. The system can build a full-resolution map using the map-sharing feature, with over 95 % of bandwidth reduction from raw sensor data.

翻译：感知仍然是未知环境中自主导航（尤其是飞行器）的一个具有挑战性的问题。大多数用于自主导航的建图算法都是专门为其特定任务设计的，这限制了其扩展使用或协作任务。本文提出了一种体素建图系统，能够为多种任务构建适应性地图。该系统采用基于哈希表的地图结构，并通过空间和时间优先级管理每个体素，无需显式地图边界。我们还引入了一种高效的地图共享功能，以最小带宽实现多智能体应用。我们在真实世界和仿真环境中测试了该系统，将其应用于包括局部建图、全局建图、协作多智能体导航和高速导航在内的多种任务。我们的系统证明了其能够构建高分辨率、广覆盖范围且具有实时性能的可定制地图，且不受传感器和环境的影响。该系统可利用地图共享功能构建全分辨率地图，与原始传感器数据相比，带宽减少超过95%。