A Small Form Factor Aerial Research Vehicle for Pick-and-Place Tasks with Onboard Real-Time Object Detection and Visual Odometry

TL;DR

This paper presents a compact aerial vehicle platform capable of onboard real-time object detection and visual odometry, achieving high success rates in pick-and-place tasks in constrained environments.

Contribution

It introduces a small form-factor aerial vehicle with custom hardware and software for onboard object detection, pose estimation, and grasping, with open-source designs for broader adoption.

Findings

93% success rate in grasping in challenging environments

Onboard computation enables reliable pick-and-place tasks

Hardware and software are openly available for replication

Abstract

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.