Development of Intelligent Unmanned Aerial Vehicles with Effective Sense and Avoid Capabilities

Ph.DDOCTOR OF PHILOSOPH

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

NAVIGATION AND AUTONOMOUS CONTROL OF MAVS IN GPS-DENIED ENVIRONMENTS

Ph.DDOCTOR OF PHILOSOPH

Indoor navigation systems for unmanned aerial vehicles

Ph.DDOCTOR OF PHILOSOPH

Use Of Drones in an Underground Mine for Geotechnical Monitoring

Geotechnical monitoring is a significant aspect of mining. This includes traditional monitoring with extensometers and stress meters, as well as new technologies which include Lidar, Radar, advanced wireless sensors, and many other new technologies. Underground mining has unique and significant safety hazards compared to surface mining, due to high stress concentrations, weak rock masses, and limited access and air quality. Underground mining methods that utilize large open stopes is one example. After each production blast in open stopes, for example, the rock can become unstable due to excessive vibrations. Since not all the areas inside stopes are accessible, it can be unsafe to put costly production equipment like Load Haul Dump (LHD) vehicles and drilling jumbos inside the stopes. Secondary blasting also becomes hazardous as it requires mining personnel to enter hazardous areas. Traditional monitoring equipment for stope monitoring is ineffective and impractical in most cases, due to the difficulties in placing the monitoring equipment inside unsafe areas of the stopes. The use of a drone can improve safety compared to other surveying systems. In addition, underground monitoring utilizing drones delivers fast results, gives real-time results, and minimizes human exposure in unsafe underground conditions. The mining industry already is benefiting from the rapidly advancing drone technologies. However, most of the drone use now is for is for surface mining, and its use in underground mining is still an area that needs significant research and development. A drone stabilizes itself using GPS, but in certain places and locations, this is not always possible; for example, under a bridge, inside a building or in an underground mine. Also, it is not safe for human personnel to enter all locations in a mine because areas can be dangerous due to loose hanging rocks and unsafe air quality. The unavailability of GPS, the low light conditions, and the confined spaces make it very difficult and challenging to use drones in an underground space, and hence University research in this area is both important and necessary. The research described in this thesis includes the following four areas: 1. Purchasing a drone and demonstrating that it can be controlled and used to capture images in an underground environment with confined space. 2. Developing a solution for drones to work in the dark underground mine environment with the use of specially designed lights attached to the drone. 3. Optimizing the settings in the drone camera to capture images of significant quality and quantity to producing high-density three-dimensional point clouds. 4. Demonstrating that the point clouds produced from underground drone monitoring are enough to extract geotechnical rock mass characteristics and rock mass movement using point cloud processing programs

Comprehensive review on controller for leader-follower robotic system

985-1007This paper presents a comprehensive review of the leader-follower robotics system. The aim of this paper is to find and elaborate on the current trends in the swarm robotic system, leader-follower, and multi-agent system. Another part of this review will focus on finding the trend of controller utilized by previous researchers in the leader-follower system. The controller that is commonly applied by the researchers is mostly adaptive and non-linear controllers. The paper also explores the subject of study or system used during the research which normally employs multi-robot, multi-agent, space flying, reconfigurable system, multi-legs system or unmanned system. Another aspect of this paper concentrates on the topology employed by the researchers when they conducted simulation or experimental studies

Flying Animal Inspired Behavior-Based Gap-Aiming Autonomous Flight with a Small Unmanned Rotorcraft in a Restricted Maneuverability Environment

This dissertation research shows a small unmanned rotorcraft system with onboard processing and a vision sensor can produce autonomous, collision-free flight in a restricted maneuverability environment with no a priori knowledge by using a gap-aiming behavior inspired by flying animals. Current approaches to autonomous flight with small unmanned aerial systems (SUAS) concentrate on detecting and explicitly avoiding obstacles. In contrast, biology indicates that birds, bats, and insects do the opposite; they react to open spaces, or gaps in the environment, with a gap_aiming behavior. Using flying animals as inspiration a behavior-based robotics approach is taken to implement and test their observed gap-aiming behavior in three dimensions. Because biological studies were unclear whether the flying animals were reacting to the largest gap perceived, the closest gap perceived, or all of the gaps three approaches for the perceptual schema were explored in simulation: detect_closest_gap, detect_largest_gap, and detect_all_gaps. The result of these simulations was used in a proof-of-concept implementation on a 3DRobotics Solo quadrotor platform in an environment designed to represent the navigational diffi- culties found inside a restricted maneuverability environment. The motor schema is implemented with an artificial potential field to produce the action of aiming to the center of the gap. Through two sets of field trials totaling fifteen flights conducted with a small unmanned quadrotor, the gap-aiming behavior observed in flying animals is shown to produce repeatable autonomous, collision-free flight in a restricted maneuverability environment. Additionally, using the distance from the starting location to perceived gaps, the horizontal and vertical distance traveled, and the distance from the center of the gap during traversal the implementation of the gap selection approach performs as intended, the three-dimensional movement produced by the motor schema and the accuracy of the motor schema are shown, respectively. This gap-aiming behavior provides the robotics community with the first known implementation of autonomous, collision-free flight on a small unmanned quadrotor without explicit obstacle detection and avoidance as seen with current implementations. Additionally, the testing environment described by quantitative metrics provides a benchmark for autonomous SUAS flight testing in confined environments. Finally, the success of the autonomous collision-free flight implementation on a small unmanned rotorcraft and field tested in a restricted maneuverability environment could have important societal impact in both the public and private sectors