This paper introduces a novel, small form-factor, aerial vehicle research platform for agile object detection, classification, tracking, and interaction tasks. General-purpose hardware components were designed to augment a given aerial vehicle and enable it to perform safe and reliable grasping. These components include a custom collision tolerant cage and low-cost Gripper Extension Package, which we call GREP, for object grasping. Small vehicles enable applications in highly constrained environments, but are often limited by computational resources. This work evaluates the challenges of pick-and-place tasks, with entirely onboard computation of object pose and visual odometry based state estimation on a small platform, and demonstrates experiments with enough accuracy to reliably grasp objects. In a total of 70 trials across challenging cases such as cluttered environments, obstructed targets, and multiple instances of the same target, we demonstrated successfully grasping the target in 93% of trials. Both the hardware component designs and software framework are released as open-source, since our intention is to enable easy reproduction and application on a wide range of small vehicles.

翻译：本文介绍了一种新型小型化空中车辆研究平台，用于敏捷目标检测、分类、跟踪及交互任务。我们设计了通用硬件组件以增强现有空中车辆的抓取能力，使其能够安全可靠地执行抓取操作。这些组件包括定制的抗碰撞保护笼和低成本抓取器扩展包（称为GREP），用于目标抓取。小型车辆虽能适应高度受限环境，但常受计算资源制约。本研究评估了在小型平台上完全依靠机载计算实现目标位姿估计与基于视觉里程计的状态估计所面临的挑战，并展示了足以可靠抓取目标的实验精度。在70次涵盖杂乱环境、目标遮挡及多目标干扰等复杂场景的试验中，目标抓取成功率达93%。硬件组件设计与软件框架均以开源形式发布，旨在促进其在各类小型车辆上的便捷复现与应用。