Abstract

A vision-based adaptive switching controller that uses optical flow information to avoid obstacles for micro unmanned aerial vehicles (MUAV) is proposed in this paper. To use the optical flow to indicate the distance between the MUAV and the environment, we propose an algorithm with multi-thread processing such that the optical flow information is obtained reliably and continuously in the entire camera field of view. The flying behavior of considered MUAV is regarded as a switching system when considering different flying modes during the mission of obstacle avoidance. By the required flight direction for obstacle avoidance specified by the detected optical flow, an adaptive control scheme is designed to track the required trajectory in switching modes. The simulation result shows the tracking performances of the adaptive control with the switching system. The experiment of the whole system is completed to verify the obstacle avoidance capability of our system.

Highlights

  • 3D robots have presented an increasingly prosperous market and rapid development

  • We focus on designing a novel vision-based adaptive controller for micro unmanned aerial vehicle (MUAV) obstacle avoidance

  • In the visual servoing systems [10,11], the camera is mounted on a moving platform, such as the robot arm or ground/aerial vehicle, which is usually controlled to follow the target through the feedback of the target information in the images

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Summary

Introduction

3D robots have presented an increasingly prosperous market and rapid development. In the visual servoing systems [10,11], the camera is mounted on a moving platform, such as the robot arm or ground/aerial vehicle, which is usually controlled to follow the target through the feedback of the target information in the images. We implement the obstacle avoidance task of the MUAV system on which the front camera installed, and we use the adaptive control with optical flow information. The main contributions of this work are that we use the optical flow information by the vision sensor and design an adaptive controller with the output in which the transfer function is unknown and composed of switching parameters.

Optical Flow Estimation for Detecting Obstacle
The Construction of Uniform Point Distribution
Comparison
Multi-Thread
Multi-thread
Visual
The considered decouples entire of the system and is given
Adaptive Control for Switched System
Simulation Analysis
Experimental Results with Visual Servoing
Conclusions
7–12 October
Full Text
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