Lateral control of vehicle platoons with on-board sensing and Inter-Vehicle Communication

This paper presents a lateral control strategy for a platoon of vehicles which utilises only data which can realistically be measured by each vehicle, augmented with Inter-Vehicle Communication (IVC). The control problem resembles those which exist for longitudinal control and this introduces the challenge of estimating a vehicles lateral position and velocity when direct measurement is not possible (due to lane markings being obscured by a preceding vehicle). It is shown that the associated robust controller, which we propose, exhibits string stability in the presence of sensor and actuation delays and a high fidelity simulation is conducted to verify this

Symbiotic relationship between robots - a ROS ARDrone/YouBot library

A Symbiotic relationship between robots is theoretically developed. It is characterised by sharing sensory information and tightly coordinating operational logic by taking care of each other’s needs during missions. The system is characterised by an intertwined reasoning system while having separate conditioning and execution of plans to achieve subgoals to support each other. The results are illustrated on strong operational inter-dependence of a rover and a drone through shared logical inference. The drone uses the rover as a landing pad and the rover uses the drone to complements its sensor system by information gathering. There is a GitHub library provided in association with the demonstration for generic use of adding cameras and cooperation logic to a AR.Drone 2.0 and a KUKA youBot system. The benefits of symbiotic relationship are quantitatively evaluated on the demonstration example

A model based design framework for safety verification of a semi-autonomous inspection drone

In this paper, we present a model based design approach to the development of a semi-autonomous control system for an inspection drone. The system is tasked with maintaining a set distance from the target being inspected and a constant relative pose, allowing the operator to manoeuvre the drone around the target with ease. It is essential that the robustness of the autonomous behaviour be thoroughly verified prior to actual implementation, as this will involve the flight of a large multi-rotor drone in close proximity to a solid structure. By utilising the Robotic Operating System to communicate between the autonomous controller and the drone, the same Simulink model can be used for numerical coverage testing, high fidelity simulation, offboard execution and final executable deploymen

Towards Software Based Optical Communication Methods for the Assistance of Docking Autonomous Underwater Vehicles

The use of optical communications systems is prevalent in underwater robotics when short-range data transmission is required or preferred. This paper proposes a method of producing and testing an optical communications system for use in the assistance of optical docking for autonomous underwater vehicles (AUVs). It describes how the Simulink modelling environment was used to program and simulate a model of a transmitter, which was then implemented on a microcontroller. The transmitter model implemented on hardware was then used to produce an optical signal, which was sampled, logged and used to design a receiver model in Simulink. For signalling purposes, the experiment used a light-emitting diode (LED) with a driver circuit and photodiode based receiver. This simulated approach using real world data enabled the analysis of the system at every point during the process, allowing for a hardware in the loop style approach to be used in the receiver model design. Consequently, the Simulink Coder was used to produce the receiver model’s equivalent in C++ for later deployment. A benchmark was determined through experimentation to compare within future studies; the system was tested and found to operate effectively at distances between 1 m and 12 m in a controlled in air test environment

Quantifying situation awareness for small unmanned aircraft Towards routine Beyond Visual Line Of Sight operations

A novel statistical model is presented to quantify situation awareness in the operation of small civilian Unmanned Aircraft Systems (UAS). Today, the vast majority of small UAS operation takes place under Visual Line Of Sight (VLOS) of a human operator, who is wholly responsible for the safety of the flight. As operation begins to move to Beyond Visual Line Of Sight (BVLOS), it is likely that this responsibility will become shared between operator and the increasingly autonomous UAS itself. Before we seek to quantify the safety of such a system, it is beneficial to analyse the safety of existing VLOS operations to provide a target level of safety. Prior to considering any on-board decision making, it is essential to ensure that the artificial situation awareness system of a UAS in BVLOS is at least as good as awareness of a human operator. The paper provides a probabilistic theory and model for the high level abstractions of situation awareness to guide future assessment of BVLOS operations

Addressing environmental and atmospheric challenges for capturing high-precision thermal infrared data in the field of astro-ecology

Using thermal infrared detectors mounted on drones, and applying techniques from astrophysics, we hope to support the field of conservation ecology by creating an automated pipeline for the detection and identification of certain endangered species and poachers from thermal infrared data. We test part of our system by attempting to detect simulated poachers in the field. Whilst we find that we can detect humans hiding in the field in some types of terrain, we also find several environmental factors that prevent accurate detection, such as ambient heat from the ground, absorption of infrared emission by the atmosphere, obscuring vegetation and spurious sources from the terrain. We discuss the effect of these issues, and potential solutions which will be required for our future vision for a fully automated drone-based global conservation monitoring system

Thermal-Drones as a Safe and Reliable Method for Detecting Subterranean Peat Fires

Underground peat fires are a major hazard to health and livelihoods in Indonesia, and are a major contributor to carbon emissions globally. Being subterranean, these fires can be difficult to detect and track, especially during periods of thick haze and in areas with limited accessibility. Thermal infrared detectors mounted on drones present a potential solution to detecting and managing underground fires, as they allow large areas to be surveyed quickly from above and can detect the heat transferred to the surface above a fire. We present a pilot study in which we show that underground peat fires can indeed be detected in this way. We also show that a simple temperature thresholding algorithm can be used to automatically detect them. We investigate how different thermal cameras and drone flying strategies may be used to reliably detect underground fires and survey fire-prone areas. We conclude that thermal equipped drones are potentially a very powerful tool for surveying for fires and firefighting. However, more investigation is still needed into their use in real-life fire detection and firefighting scenarios

Successful observation of orangutans in the wild with thermal-equipped drones

We investigated the efficacy of a drone equipped with a thermal camera as a potential survey tool to detect wild Bornean orangutans (Pongo pygmaeus) and other tropical primates. Using the thermal camera we successfully detected 41 orangutans and a troop of proboscis monkeys, all of which were confirmed by ground observers. We discuss the potential advantages and limitations of thermal-equipped drones as a tool to complement other methods, and the potential of this technology for use as a future survey tool

Requirements and Limitations of Thermal Drones for Effective Search and Rescue in Marine and Coastal Areas

Search and rescue (SAR) is a vital line of defense against unnecessary loss of life. However, in a potentially hazardous environment, it is important to balance the risks associated with SAR action. Drones have the potential to help with the efficiency, success rate and safety of SAR operations as they can cover large or hard to access areas quickly. The addition of thermal cameras to the drones provides the potential for automated and reliable detection of people in need of rescue. We performed a pilot study with a thermal-equipped drone for SAR applications in Morecambe Bay. In a variety of realistic SAR scenarios, we found that we could detect humans who would be in need of rescue, both by the naked eye and by a simple automated method. We explore the current advantages and limitations of thermal drone systems, and outline the future path to a useful system for deployment in real-life SAR