The mining industry is constantly under pressure to improve productivity, effciency and safety. Although an increased use of automation technology has the potential of con- tributing to improvements in all three factors mines have been relatively slow to make use of automation technology. Automation in the underground mining environment is a challenging prospect for a number of reasons not least of which being the diffculties and associated costs of installing infrastructure in this hazardous environment. The work described in this dissertation focuses on the modelling of a Load-Haul-Dump or LHD vehicle for the purpose of autonomous navigation and control. Considerable progress has been made in automating underground mining vehicles in recent years, and successful test installations have been made. There are still however a number of shortcomings in the existing autonomous underground mine vehicle navigation systems. This dissertation attempts to address some of these problems through the development of a more accurate vehicle model for an LHD vehicle incorporating some vehicle and tyre dynamics thereby potentially reducing the number of sensors and the amount of installed infrastructure necessary to implement the vehicle navigation system. Simulation results are provided for different vehicle modelling techniques and the results are compared and discussed in terms of their suitability for physical implementation in an underground mine. / Dissertation (MEng (Electronic Engineering))--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / MEng / unrestricted

The United States Army has moved into the 21st century with the intent of redesigning not only the force structure but also the methods by which we will fight and win our nation's wars. Fundamental in this restructuring is the development of the Future Combat Systems (FCS). In an effort to minimize exposure of front line soldiers the future Army will utilize unmanned assets for both information gathering and when necessary engagements. Yet this must be done judiciously, as the bandwidth for net-centric warfare is limited. The implication is that the FCS must be designed to leverage bandwidth in a manner that does not overtax computational resources. In this study alternatives for improving human performance during operation of teleoperated and semi-autonomous robots were examined. It was predicted that when operating both types of robots, frame delay of the semi-autonomous robot would improve performance because it would allow operators to concentrate on the constant workload imposed by the teleoperated while only allocating resources to the semi-autonomous during critical tasks. An additional prediction was that operators with high spatial ability would perform better than those with low spatial ability, especially when operating an aerial vehicle. The results can not confirm that frame delay has a positive effect on operator performance, though power may have been an issue, but clearly show that spatial ability is a strong predictor of performance on robotic asset control, particularly with aerial vehicles. In operating the UAV, the high spatial group was, on average, 30% faster, lazed 12% more targets, and made 43% more location reports than the low spatial group. The implications of this study indicate that system design should judiciously manage workload and capitalize on individual ability to improve performance and are relevant to system designers, especially in the military community.

The focus of this dissertation is to improve autonomous navigation in unstructured terrain conditions, with specific application to unmanned casualty extraction in disaster scenarios. Robotic systems are being widely employed for search and rescue applications, especially in disaster scenarios. But a majority of these are focused solely on the search aspect of the problem. This dissertation proposes a conceptual design of a Semi-Autonomous Victim Extraction Robot (SAVER) capable of safe and effective unmanned casualty extraction, thereby reducing the risk to the lives of first responders. In addition, the proposed design addresses the limitations of existing state-of-the-art rescue robots specifically in the aspect of head and neck stabilization as well as fast and safe evacuation. One of the primary capabilities needed for effective casualty extraction is reliable navigation in unstructured terrain conditions. Autonomous navigation in unstructured terrain, particularly for systems with tracked locomotion mode involves unique challenges in path planning and trajectory tracking. The dynamics of robot-terrain interaction, along with additional factors such as slip experienced by the vehicle, slope of the terrain, and actuator limitations of the robotic system, need to be taken into consideration. To realize these capabilities, this dissertation proposes a hybrid navigation architecture that employs a physics engine to perform fast and accurate state expansion inside a graph-based planner. Tracked skid-steer systems experience significant slip, especially while turning. This greatly affects the trajectory tracking accuracy of the robot. In order to enable efficient trajectory tracking in varying terrain conditions, this dissertation proposes the use of an active disturbance rejection controller. The proposed controller is capable of estimating and counter acting the effects of slip in real-time to improve trajectory tracking. As an extension of the above application, this dissertation also proposes the use of support vector machine architecture to perform terrain identification, solely based on the estimated slip parameters. Combining all of the above techniques, an overall architecture is proposed to assist and inform tele-operation of tracked robotic systems in unstructured terrain conditions. All of the above proposed techniques have been validated through simulations and experiments in indoor and simple outdoor terrain conditions. / Doctor of Philosophy / This dissertation explores ways to improve autonomous navigation in unstructured terrain conditions, with specific applications to unmanned casualty extraction in disaster scenarios. Search and rescue applications often put the lives of first responders at risk. Using robotic systems for human rescue in disaster scenarios can keep first responders out of danger. To enable safe robotic casualty extraction, this dissertation proposes a novel rescue robot design concept named SAVER. The proposed design concept consists of several subsystems including a declining stretcher bed, head and neck support system, and robotic arms that conceptually enable safe casualty manipulation and extraction based on high-level commands issued by a remote operator. In order to enable autonomous navigation of the proposed conceptual system in challenging outdoor terrain conditions, this dissertation proposes improvements in planning, trajectory tracking control and terrain estimation. The proposed techniques are able to take into account the dynamic effects of robot-terrain interaction including slip experienced by the vehicle, slope of the terrain and actuator limitations. The proposed techniques have been validated through simulations and experiments in indoor and simple outdoor terrain conditions. The applicability of the above techniques in improving tele-operation of rescue robotic systems in unstructured terrain is also discussed at the end of this dissertation.