Improving Optical Flow Sensor Using a Gimbal for Quadrotor Navigation in GPS-Denied Environment

This paper proposes a new sensor using optical flow to stabilize a quadrotor when a GPS signal is not available. Normally, optical flow varies with the attitude of the aerial vehicle. This produces positive feedback on the attitude control that destabilizes the orientation of the vehicle. To avoid this, we propose a novel sensor using an optical flow camera with a 6DoF IMU (Inertial Measurement Unit) mounted on a two-axis anti-shake stabilizer mobile aerial gimbal. We also propose a robust algorithm based on Sliding Mode Control for stabilizing the optical flow sensor downwards independently of the aerial vehicle attitude. This method improves the estimation of the position and velocity of the quadrotor. We present experimental results to show the performance of the proposed sensor and algorithms.

Design and Implementation of Attitude Stabilization System for Marine Satellite Tracking Antenna

Marine Satellite Tracking Antenna (MSTA) is an important shipboard device for ships to bidirectionally communicate with the outside. The attitude stabilization system is an important part of MSTA for keeping the antenna dish tracking the geostationary satellite in the presence of severe ship dynamics. In this paper, the designed high-performance attitude stabilization system is introduced, including hardware system, model identification and controller design. The detailed procedure for identifying the stepper motor model is stated, which is different from conventional procedure. The design procedure of the robust controller based on H ∞ loop shaping is given. The designed attitude stabilization system was tested on a Stewart platform that was used as the ship simulator. From the testing results, it can be seen that the performance of designed attitude stabilization system is very high and the tracking angle error can be limited to within ± 0.15 deg, which satisfies the performance requirements of Ka-band MSTA product.

Haptic feedback and visual servoing of teleoperated unmanned aerial vehicle for obstacle awareness and avoidance

Obstacle avoidance represents a fundamental challenge for unmanned aerial vehicle navigation. This is particularly relevant for low altitude flight, which is highly subjected to collisions, causing property damage or even compromise human safety. Autonomous navigation algorithms address this problem and are applied in various tasks. However, this approach is usually overshadowed by unreliable results in uncertain environments. In contrast, human pilots are able to maneuver vehicles in complex situations, in which an algorithm would no offer a reliable performance. This article explores a novel configuration of assisted flying and implements an experimental setup in order to prove its efficacy. The user controls an unmanned aerial vehicle with a force feedback device, where simultaneously an assisted navigation algorithm can manipulate this apparatus to divert the unmanned aerial vehicle from its path. Experiments confirm the authors’ hypothesis that the unmanned aerial vehicle is deviated or maintains the same course at the operator’s will. Unlike conventional controllers that dictate roll, pitch, and yaw, this implementation uses direct mapping between the position represented by the haptic device and the unmanned aerial vehicle. This configuration applies feedback before the unmanned aerial vehicle has reached the position referenced by the haptic device, providing valuable time for the user to make the necessary path correction.

Vision-based autonomous hovering for a miniature quad-rotor

In this paper, a vision-based scheme for the autonomous hovering of a miniature quad-rotor is developed. Cameras are used to estimate the position and the translational velocity of the vehicle. The dynamic model of the miniature quad-rotor is developed using the Newton–Euler approach. A nonlinear controller based on a separated saturation control strategy for a miniature quad-rotor is presented. To validate the theoretical results, an embedded control system for the miniature quad-rotor has been developed. Thus, the analytic results are supported by experimental tests. Experimental results have validated the proposed control strategy.

Visual servoing applied to real-time stabilization of a multi-rotor UAV

In this paper we address the problem of stabilization and local positioning of a four-rotor rotorcraft using computer vision. Our approaches to estimate the orientation and position of the rotorcraft combine the measurements from an Inertial Measurement Unit (IMU) and a vision system composed of a single camera. In the first stage, the vision system is used to estimate the position and yaw angle of the rotorcraft, while in the second stage the vision system is used to estimate the translational velocity of the flying robot. In both cases the IMU gives the pitch and roll angles at a higher rate. The technique used to estimate the position of the rotorcraft in the first stage combines the homogeneous transformation approach for the camera calibration process with the plane-based pose method for estimating the position. In the second stage, a navigation system using the optical flow is also developed to estimate the translational velocity of the aircraft. We present real-time experiments of stabilization and location of a four-rotor rotorcraft.