Autonomous Vision-Based Aerial Grasping for Rotorcraft Unmanned Aerial Vehicles.

Lishan Lin,Xuechen Chen,Yuji Yang,Hui Cheng

doi:10.3390/s19153410

Abstract

Autonomous vision-based aerial grasping is an essential and challenging task for aerial manipulation missions. In this paper, we propose a vision-based aerial grasping system for a Rotorcraft Unmanned Aerial Vehicle (UAV) to grasp a target object. The UAV system is equipped with a monocular camera, a 3-DOF robotic arm with a gripper and a Jetson TK1 computer. Efficient and reliable visual detectors and control laws are crucial for autonomous aerial grasping using limited onboard sensing and computational capabilities. To detect and track the target object in real time, an efficient proposal algorithm is presented to reliably estimate the region of interest (ROI), then a correlation filter-based classifier is developed to track the detected object. Moreover, a support vector regression (SVR)-based grasping position detector is proposed to improve the grasp success rate with high computational efficiency. Using the estimated grasping position and the UAV?Äôs states, novel control laws of the UAV and the robotic arm are proposed to perform aerial grasping. Extensive simulations and outdoor flight experiments have been implemented. The experimental results illustrate that the proposed vision-based aerial grasping system can autonomously and reliably grasp the target object while working entirely onboard.

Highlights

There is increasing interests in unmanned aerial vehicles (UAVs) within both the industrial and academic communities
These challenging problems mainly come from the following aspects: (1) the limitation imposed by the high-order underactuated control systems; (2) the limited onboard vision-based sensing; (3) highly computational efficiency of visual detection, estimation of grasping points of the target object, and control of the UAV equipped with a robotic arm are required for onboard implementation using a low-cost embedded controller; (4) coupling between perception and control of the aerial manipulation system
Motived by the challenging problems, we systematically investigate a vision-based strategy to perform aerial grasping by an UAV

Summary

Introduction

There is increasing interests in unmanned aerial vehicles (UAVs) within both the industrial and academic communities. With the high 3-D mobility, UAVs act like smart flying cameras in passive observation applications. A UAV equipped with a robotic arm can perform aerial manipulation tasks like grasping, placing and pushing objects [3]. Vision-based aerial manipulation for micro UAVs poses challenges due to the inherent instability of the UAVs, limited onboard sensing and computational capabilities, and aerodynamic disturbances in close contact. There are some challenges for UAVs to perform autonomous vision-based aerial grasping. These challenging problems mainly come from the following aspects:

Objectives

Methods

Results

Conclusion