Incorporation of acoustic sensors in the regulation of a mobile robot

This article introduces the incorporation of acoustic sensors for the localization of a mobile robot. The robot is considered as a sound source and its position is located applying a Time Delay of Arrival (TDOA) method. Since the accuracy of this method varies with the microphone array, a navigation acoustic map that indicates the location errors is built. This map also provides the robot with navigation trajectories point-to-point and the control is capable to drive the robot through these trajectories to a desired configuration. The proposed localization method is thoroughly tested using both a 900 Hz square signal and the natural sound of the robot, which is driven near the desired point with an average error of 0:067 m.This is an Accepted Manuscript of an article published by Taylor & Francis in Advanced Robotics on 01/01/2019, available online: http://www.tandfonline.com/10.1080/01691864.2019.1573703.”Peer ReviewedPostprint (author's final draft

Vision based leader-follower formation control for mobile robots

Creating systems with multiple autonomous vehicles places severe demands on the design of control schemes. Robot formation control plays a vital role in coordinating robots. As the number of members in a system rise, the complexity of each member increases. There is a proportional increase in the quantity and complexity of onboard sensing, control and computation. This thesis investigates the control of a group of mobile robots consisting of a leader and several followers to maintain a desired geometric formation --Abstract, page iii

Analysis of Mobile Laser Scanning (MLS) Ground Control Methods and Achievable Accuracies

The surveying techniques using LiDAR have been recognised as a platform that is increasingly becoming popular and evolving within the spatial science profession. As survey job sites continue to grow in size and the need for quick collection of data, mobile laser scanning techniques are exponentially growing. This presents a problem in regards to the accuracies that are being achieved and what the data is fit for. This paper has a particular focus in regards to mobile laser scanning ground control and what level of accuracy can be expected from the level of ground control implemented. A variety of ground control geometries and quantities were developed to be tested against a traditional total station survey. The data points collected in each scenario where directly compared to the same point collected from the total station. The data obtained allowed me to calculate confidence intervals and the accuracy range in which the data should achieve if the experiment were to be replicated. The direct point versus point comparison allowed me to determine which scenario was the closest in accuracy to a total station survey and if there was any scenario which replicated a total station survey. The project returned results in which can be used to determine what can be expected from mobile laser scanning with a certain level of ground control. The project developed eight different ground control scenarios with varying results. The most dense and accurate scenario from the mobile laser scanning was horizontally 34.5mm from the total station survey position, whilst the scenario with no ground control at all was 59mm from the total station survey. There was very limited movement throughout the scenarios in regards to the vertical accuracy, all returned accuracies within 31.5mm-39mm from the total station survey. It would be recommended to that densifying the control exponentially does not return accuracies which can be treated as a total station survey. The extra time and costs associated with densifying the control far outweighs the accuracies improvements which can be achieved. It should also be highlighted that mobile laser scanning surveys with no ground control produces usable data. Uncontrolled MLS surveys should only be used for surveys where accuracies better than 50mm are not trying to be achieved; the only downfall of uncontrolled MLS surveys is the lack of redundant data for validation. Overall the results from the project satisfied the aims and objectives of this research project. The results are discussed in much more depth throughout the paper and recommendations and future research prospects have been discussed

Simultaneous localization and odometry calibration for mobile robot

International audienceThis paper presents both the theory and the first experimental results of a new method which allows simultaneous estimation of the robot configuration and the odometry error (both systematic and non-systematic) during the mobile robot navigation. The estimation of the non-systematic components is carried out through an augmented Kalman filter which estimates a state containing the robot configuration and the parameters of the odometry error. It uses encoder readings as inputs and the readings from a laser range finder as observations. The estimation of the non-systematic components is carried out through another Kalman filter where the observations are obtained by two subsequent robot configurations provided by the previous augmented Kalman filter