论文标题
ASAP：用于在线处理基于事件算法的自适应传输方案
ASAP: Adaptive Transmission Scheme for Online Processing of Event-based Algorithms
论文作者
论文摘要
董事会机器人基于在线事件的感知技术在复杂，非结构化和动态的环境中导航可能会遭受不可预测的事件速率及其处理时间的变化，这可能会导致计算溢出或响应损失。本文提出了尽快的：一种新型的事件处理框架，该框架将事件传输到处理算法，保持系统响应能力并防止溢出。尽快由两个自适应机制组成。第一个通过丢弃传入事件的自适应百分比来防止事件处理溢出。第二种机制动态调整事件软件包的大小，以减少事件生成和处理之间的延迟。尽快保证了收敛性，并且对处理算法具有灵活性。它已在具有挑战性的条件下在船上验证了四型和鸟类机器人的机器人。
Online event-based perception techniques on board robots navigating in complex, unstructured, and dynamic environments can suffer unpredictable changes in the incoming event rates and their processing times, which can cause computational overflow or loss of responsiveness. This paper presents ASAP: a novel event handling framework that dynamically adapts the transmission of events to the processing algorithm, keeping the system responsiveness and preventing overflows. ASAP is composed of two adaptive mechanisms. The first one prevents event processing overflows by discarding an adaptive percentage of the incoming events. The second mechanism dynamically adapts the size of the event packages to reduce the delay between event generation and processing. ASAP has guaranteed convergence and is flexible to the processing algorithm. It has been validated on board a quadrotor and an ornithopter robot in challenging conditions.
