ASAP：用于基于事件的算法在线处理的自适应传输方案
ASAP: Adaptive Transmission Scheme for Online Processing of Event-based Algorithms
AI总结：
针对机器人在线事件感知因事件速率和处理时间变化导致的溢出与响应延迟问题，提出包含自适应事件丢弃和事件包大小调整的 ASAP 框架，并在四旋翼与扑翼机器人上验证。
摘要：
在复杂、非结构化和动态环境中导航的机器人机载在线基于事件的感知技术，可能会遭遇输入事件速率及其处理时间的不可预测变化，从而导致计算溢出或响应性丧失。本文提出了 ASAP：一种新颖的事件处理框架，可动态调整事件向处理算法的传输，保持系统响应性并防止溢出。ASAP 由两种自适应机制组成。第一种机制通过丢弃自适应比例的输入事件来防止事件处理溢出。第二种机制动态调整事件包的大小，以减少事件生成与处理之间的延迟。ASAP 具有收敛保证，并且对处理算法具有灵活性。它已在具有挑战性的条件下于四旋翼飞行器和扑翼机器人上得到验证。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
