Haiyang Chao

Autopilots for Small Fixed-Wing Unmanned Air Vehicles: A Survey

This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.This paper presents a survey of the autopilot systems for small fixed-wing unmanned air vehicles (UAVs). The UAV flight control basics are introduced first. The radio control system and autopilot control system are then explained from both hardware and software viewpoints. Several typical commercial off-the-shelf autopilot packages are compared in detail. In addition, some research autopilot systems are introduced. Finally, conclusions are made with a summary of the current autopilot market and a remark on the future development.

Band-reconfigurable Multi-UAV-based Cooperative Remote Sensing for Real-time Water Management and Distributed Irrigation Control

Abstract This paper presents an overview of ongoing research on small unmanned autonomous vehicles (UAVs) for cooperative remote sensing for real-time water management and irrigation control. Small UAVs can carry embedded cameras with different wavelength bands, which are low-cost but have high spatial-resolution. These imagers mounted on UAVs can form a camera array to perform multispectral imaging with reconfigurable bands dependent on mission. Development of essential subsystems, such as the UAV platforms, embedded multispectral imagers, and image stitching and registration, is introduced together with real UAV flight test results of one typical example mission.

Experimental Validation of Consensus Algorithms for Multivehicle Cooperative Control

In this brief, consensus algorithms are experimentally implemented and validated on a mobile actuator and sensor network platform under directed, possibly switching interaction topologies to explore issues and challenges in distributed multivehicle cooperative control. Distributed consensus algorithms are applied to two target applications including rendezvous and axial alignment. In the rendezvous application, multiple mobile robots simultaneously arrive at a common a priori unknown target location determined through team negotiation. In the axial alignment application, multiple mobile robots collectively align their final positions along a line. The experimental results show the effectiveness and robustness of the consensus algorithms even in the presence of platform physical limitations, packet loss, information delay, etc. These experimental results validate the corresponding theoretical results.

A comparative evaluation of low-cost IMUs for unmanned autonomous systems

Inertial measurement units (IMUs) are widely used for navigation and calibration purposes on unmanned autonomous vehicles. This paper provides a comparative survey and evaluation of the low-cost IMUs focusing on both the possible sensor packages and the available software solutions. Several example IMUs are compared in detail including inertial only IMUs, GPS-coupled IMUs, and hobbyist-level IMUs. The future direction of low-cost IMUs are discussed including optical-flow-based solutions and collaborative IMUs.

A Survey of Optical Flow Techniques for Robotics Navigation Applications

Optical flow has been widely used by insects and birds to support navigation functions. Such information has appealing capabilities for application to ground and aerial robots, especially for navigation and collision avoidance in urban or indoor areas. The purpose of this paper is to provide a survey of existing optical flow techniques for robotics navigation applications. Detailed comparisons are made among different optical-flow-aided navigation solutions with emphasis on the sensor hardware as well as optical flow motion models. A summary of current research status and future research directions are further discussed.

Low-cost UAV-based thermal infrared remote sensing: Platform, calibration and applications

Thermal infrared (TIR) remote sensing is recognized as a powerful tool for collecting, analyzing and modeling of energy fluxes and temperature variations. Traditional aircraft, satellite or ground TIR platforms can provide valuable regional-scale environmental information. However, these platforms have limitations, such as expensive cost, complicated manipulation, etc. In comparison, small unmanned aircraft systems (UAS) have many advantages in TIR remote sensing applications over traditional platforms. In this paper, a low-cost UAV-based TIR remote sensing platform: AggieAir-TIR is introduced. AggieAir-TIR is a small, low-cost, flexible TIR remote sensing platform, which was accomplished at the Center for Self Organizing and Intelligent Systems (CSOIS) in Utah State University (USU). The detailed introduction of AggieAir-TIR remote sensing platform is provided in the paper. Furthermore, a low-cost TIR imaging camera calibration experiment is designed, and the calibration results are provided. Based on this AggieAir-TIR remote sensing platform, many remote TIR image data collection and analysis projects can be effectively implemented.

Consensus of information in distributed control of a diffusion process using centroidal Voronoi tessellations

For the diffusion control problem, this paper considers spraying control via a group of networked mobile robots equipped with chemical neutralizers, known as smart mobile sprayers or actuators, in a domain of interest having static mesh sensor network for concentration sensing. The major contribution of this paper is the investigation of the problem of information sharing and consensus when using centroidal Voronoi tessellations algorithm to control a diffusion process. The information is shared not only on where to spray but also on how much to spray among the mobile actuators. Benefits from using information sharing and information consensus seeking are demonstrated in simulation results.

Experimental implementation and validation of consensus algorithms on a mobile actuator and sensor network platform

In this paper, we experimentally implement and validate distributed consensus algorithms on a mobile actuator and sensor network platform under directed, possibly switching interaction topologies to explore issues and challenges in distributed multi-vehicle cooperative control. Distributed consensus algorithms are applied to three target applications namely rendezvous, axial alignment, and formation maneuvering. In the rendezvous application, multiple mobile robots simultaneously arrive at a common a priori unknown target location determined through team negotiation. In the axial alignment application, multiple mobile robots collectively align their final positions along a line. In the formation maneuvering application, multiple mobile robots form a rigid geometric shape and maneuver as a group with a given group velocity. The experimental results show the effectiveness and robustness of the consensus algorithms even in the presence of platform physical limitations, packet loss, information delay, etc.

UAV Attitude, Heading, and Wind Estimation Using GPS/INS and an Air Data System

A new attitude, heading, and wind estimation algorithm is proposed, which incorporates measurements from an air data system to properly relate predicted attitude information with aircraft velocity information. Experimental Unmanned Aerial Vehicle (UAV) flight data was used to validate the proposed approach. The experimental results demonstrated effective estimation of the roll, pitch, yaw, and heading angles, and provided a smoothed estimate of the angle of attack and sideslip angles. The wind estimation results were validated with respect to measurments provided by a local weather station. It was shown that this new method of attitude estimation is effective in distinguishing the yaw and heading angles of the aircraft, properly regulating the attitude estimates with air data system measurements, and provding a reasonable estimate of the local wind field.

AggieAir: Towards low-cost cooperative multispectral remote sensing using small unmanned aircraft systems

This chapter focuses on using small low-cost unmanned aircraft systems (UAS) for remote sensing of meteorological and related conditions over agricultural fields or environmentally important land areas. Small UAS, including unmanned aerial vehicle (UAV) and ground devices, have many advantages in remote sensing applications over traditional aircraftor satellite-based platforms or ground-based probes for many applications. This is because small UAVs are easy tomanipulate, cheap tomaintain, and remove the need for human pilots to perform tedious or dangerous jobs. Multiple small UAVs can be flown in a group and complete challenging tasks such as real-time mapping of large-scale agriculture areas. The purpose of remote sensing is to acquire information about the Earth’s surface without coming into contact with it. One objective of remote sensing is to characterize the electromagnetic radiation emitted by objects (James, 2006). Typical divisions of the electromagnetic spectrum include the visible light band (380− 720nm), near infrared (NIR) band (0.72− 1.30μm), and mid-infrared (MIR) band (1.30− 3.00μm). Band-reconfigurable imagers can generate several images from different bands ranging from visible spectra to infra-red or thermal based for various applications. The advantage of an ability to examine different bands is that different combinations of spectral bands can have different purposes. For example, the combination of red-infrared can be used to detect vegetation and camouflage and the combination of red slope can be used to estimate the percent of vegetation cover (Johnson et al., 2004). Different bands of images acquired remotely through UAS could be used in scenarios like water management and irrigation control. In fact, it is difficult to sense and estimate the state of water systems because most water systems are large-scale and need monitoring of many factors including the quality, quantity, and location of water, soil and vegetations. For the mission of accurate sensing of a water system, ground probe stations are expensive to build and can only provide data with very limited sensing range (at specific positions and second level temporal resolution). Satellite photos can cover a large area, but have a low resolution and a slow update rate (30-250 meter or lower spatial resolution and week level temporal resolution). Small UAVs cost less money but can provide more accurate information (meter or centimeter spatial