Current trends in agricultural equipment have led to an increasing degree of autonomy. As the state of the art progresses towards fully autonomous vehicles, it is important to consider assumptions implicit in the design of these vehicles. Current automation in harvesters have led to increased sensing and automation on current combines, but no published research examines the effect of machine size on the viability of the autonomous system. The question this thesis examines is: if a human is no longer required to operate an individual harvester, is it possible to build smaller equipment that is still economically viable? This thesis examines the appropriateness of automating these machines by developing a conceptual model for smaller, fully autonomous harvesters. This model includes the basic mechanical subsystems, a conceptual software design, and an economic model of the total cost of ownership. The result of this conceptual design and analysis is a greater understanding of the role of autonomy in harvest. By comparing machine size, machine function, and the costs to own and operate this equipment, design guidelines for future autonomous systems are better understood. It is possible to build an autonomous harvesting system that can compete with current technologies in both harvest speed and overall cost of ownership. / Master of Science

University of Technology, Sydney. Faculty of Engineering. / The thesis focuses on issues of vehicle modelling incorporating wheel-terrain interaction and low-level control design taking into account uncertainties and input time delay. Addressing these issues is of significant importance in achieving persistent autonomy for outdoor UGVs, especially when navigating on unprepared terrains. The test-bed vehicle used for this research is retrofitted from an all-terrain 20-hp, 0.5-tonne vehicle. Its driveline system consists of an internal combustion engine, continuous variable transmission (CVT), gearbox, differential, chains, and eight wheels. The vehicle is driven in the skid-steering mode, which is popular for many off-road land-vehicle platforms. In this thesis, a comprehensive approach is proposed for modelling the driveline. The approach considers the difference in speed between two outputs of the differential and the turning mechanism of the vehicle. It describes dynamics of all components in the vehicle driveline in an integrated manner with the vehicle motion. Given a pattern of the throttle position, left and right braking efforts as the inputs, the dynamic behaviour of the wheels and other components of the UGV can be predicted. For controlling the vehicle at the low level, PID controllers are firstly used for all actuators. As many components of the vehicle exhibit nonlinearities and time delay, the large overshoots encountered in the outputs can lead to undesirable vehicle behaviours. To alleviate the problem, a novel control approach is proposed for suppression of overshoots resulting from PID control. Sliding mode control (SMC) is employed, for this, with time delay compensated by using an output predictor. As a result, the proposed approach can improve significantly system robustness and reduce substantially step response overshoot. Notably, the design is generic in that it can be applied for many dynamic processes. Knowledge of the interaction between the UGV and the terrain plays an important role in increasing its autonomy and securing the safety for off-road locomotion. In this regard, vehicle kinematic equations are combined with the theory of terramechanics for dynamic modelling of the interaction between the vehicle wheels and a variety of terrain types. Also, a fast algorithm is developed to enable online implementation. The novel interaction model takes into account the relationship between normal stresses, shear stresses, and shear displacement of the terrain that is in contact with the wheels in deriving the three-dimensional reaction forces. Finally, all modelling and control algorithms are integrated into a unique simulator for emulating the vehicle mobility characteristics. In particular, the wheel’s slip and rolling resistance can also be derived to provide useful information for closed-loop control when the UGV is navigating in an unknown environment. The simulator, as a tool for analysing the vehicle mobility, is helpful for further research on relevant topics such as traction control, safe and effective locomotion.

University of Technology, Sydney. Faculty of Engineering. / The thesis focuses on issues of vehicle modelling incorporating wheel-terrain interaction and low-level control design taking into account uncertainties and input time delay. Addressing these issues is of significant importance in achieving persistent autonomy for outdoor UGVs, especially when navigating on unprepared terrains. The test-bed vehicle used for this research is retrofitted from an all-terrain 20-hp, 0.5-tonne vehicle. Its driveline system consists of an internal combustion engine, continuous variable transmission (CVT), gearbox, differential, chains, and eight wheels. The vehicle is driven in the skid-steering mode, which is popular for many off-road land-vehicle platforms. In this thesis, a comprehensive approach is proposed for modelling the driveline. The approach considers the difference in speed between two outputs of the differential and the turning mechanism of the vehicle. It describes dynamics of all components in the vehicle driveline in an integrated manner with the vehicle motion. Given a pattern of the throttle position, left and right braking efforts as the inputs, the dynamic behaviour of the wheels and other components of the UGV can be predicted. For controlling the vehicle at the low level, PID controllers are firstly used for all actuators. As many components of the vehicle exhibit nonlinearities and time delay, the large overshoots encountered in the outputs can lead to undesirable vehicle behaviours. To alleviate the problem, a novel control approach is proposed for suppression of overshoots resulting from PID control. Sliding mode control (SMC) is employed, for this, with time delay compensated by using an output predictor. As a result, the proposed approach can improve significantly system robustness and reduce substantially step response overshoot. Notably, the design is generic in that it can be applied for many dynamic processes. Knowledge of the interaction between the UGV and the terrain plays an important role in increasing its autonomy and securing the safety for off-road locomotion. In this regard, vehicle kinematic equations are combined with the theory of terramechanics for dynamic modelling of the interaction between the vehicle wheels and a variety of terrain types. Also, a fast algorithm is developed to enable online implementation. The novel interaction model takes into account the relationship between normal stresses, shear stresses, and shear displacement of the terrain that is in contact with the wheels in deriving the three-dimensional reaction forces. Finally, all modelling and control algorithms are integrated into a unique simulator for emulating the vehicle mobility characteristics. In particular, the wheel’s slip and rolling resistance can also be derived to provide useful information for closed-loop control when the UGV is navigating in an unknown environment. The simulator, as a tool for analysing the vehicle mobility, is helpful for further research on relevant topics such as traction control, safe and effective locomotion.

Presently in ground vehicle industries, conducting durability tests with a high acceleration factor have become increasingly demanding for the less time and cost involvement. In the previous work, to accelerate the field test, the standard ‘test tailoring’ approach has been modified due to the requirement of high acceleration factors and the limitations of testing implementation. In this study, a computer-aided testing method is developed for the validation of this modified approach. Hence, a new test-piece has been designed by a conjugative approach involving the finite element technique and fatigue analysis. Afterwards, the accelerated durability loading profiles synthesized via the modified approach have been applied on the designed test-piece and the fatigue life has been simulated to verify the effectiveness of those loading profiles. Simulation results show that loading profiles with an acceleration factor up to 330 can be successfully generated with an accuracy of 95% by this modified approach.

Presently in ground vehicle industries, conducting durability tests with a high acceleration factor have become increasingly demanding for the less time and cost involvement. In the previous work, to accelerate the field test, the standard ‘test tailoring’ approach has been modified due to the requirement of high acceleration factors and the limitations of testing implementation. In this study, a computer-aided testing method is developed for the validation of this modified approach. Hence, a new test-piece has been designed by a conjugative approach involving the finite element technique and fatigue analysis. Afterwards, the accelerated durability loading profiles synthesized via the modified approach have been applied on the designed test-piece and the fatigue life has been simulated to verify the effectiveness of those loading profiles. Simulation results show that loading profiles with an acceleration factor up to 330 can be successfully generated with an accuracy of 95% by this modified approach.

University of Technology, Sydney. Faculty of Engineering. / The thesis focuses on issues of vehicle modelling incorporating wheel-terrain interaction and low-level control design taking into account uncertainties and input time delay. Addressing these issues is of significant importance in achieving persistent autonomy for outdoor UGVs, especially when navigating on unprepared terrains. The test-bed vehicle used for this research is retrofitted from an all-terrain 20-hp, 0.5-tonne vehicle. Its driveline system consists of an internal combustion engine, continuous variable transmission (CVT), gearbox, differential, chains, and eight wheels. The vehicle is driven in the skid-steering mode, which is popular for many off-road land-vehicle platforms. In this thesis, a comprehensive approach is proposed for modelling the driveline. The approach considers the difference in speed between two outputs of the differential and the turning mechanism of the vehicle. It describes dynamics of all components in the vehicle driveline in an integrated manner with the vehicle motion. Given a pattern of the throttle position, left and right braking efforts as the inputs, the dynamic behaviour of the wheels and other components of the UGV can be predicted. For controlling the vehicle at the low level, PID controllers are firstly used for all actuators. As many components of the vehicle exhibit nonlinearities and time delay, the large overshoots encountered in the outputs can lead to undesirable vehicle behaviours. To alleviate the problem, a novel control approach is proposed for suppression of overshoots resulting from PID control. Sliding mode control (SMC) is employed, for this, with time delay compensated by using an output predictor. As a result, the proposed approach can improve significantly system robustness and reduce substantially step response overshoot. Notably, the design is generic in that it can be applied for many dynamic processes. Knowledge of the interaction between the UGV and the terrain plays an important role in increasing its autonomy and securing the safety for off-road locomotion. In this regard, vehicle kinematic equations are combined with the theory of terramechanics for dynamic modelling of the interaction between the vehicle wheels and a variety of terrain types. Also, a fast algorithm is developed to enable online implementation. The novel interaction model takes into account the relationship between normal stresses, shear stresses, and shear displacement of the terrain that is in contact with the wheels in deriving the three-dimensional reaction forces. Finally, all modelling and control algorithms are integrated into a unique simulator for emulating the vehicle mobility characteristics. In particular, the wheel’s slip and rolling resistance can also be derived to provide useful information for closed-loop control when the UGV is navigating in an unknown environment. The simulator, as a tool for analysing the vehicle mobility, is helpful for further research on relevant topics such as traction control, safe and effective locomotion.

Unmanned ground vehicles are increasingly employing a combination of active sensors such as LIDAR with passive sensors like cameras to perform at all levels of perception, which includes detection, recognition and classification. Typical cameras measure the intensity of light at a variety of different wavelengths to classify objects in different areas of an image. A polarimetric camera not only measures intensity of light, but can also determine its state of polarization. The polarization of light is the angle the electric field of the wave of light takes as it travels. A polarimetric camera can identify the state of polarization of the light, which can be used to segment highly polarizing areas in a natural environment, such the surface of water. The polarimetric camera designed and built for this thesis was created with low cost in mind, as commercial polarimetric cameras are very expensive. It uses multiple beam splitters to split incoming light into four machine vision cameras. In front of each machine vision camera is a linear polarizing filter that is set to a specific orientation. Using the data from each camera, the Stokes vector can be calculated on a pixel by pixel basis to determine what areas of the image are more polarized. Test images of various scenes that included running water, standing water, mud, and vehicles showed promise in using polarization data to highlight and identify areas of interest. This data could be used by a UGV to make more informed decisions in an autonomous navigation mode. / Master of Science

Perception is a key feature in how any creature or autonomous system relates to its environment. While there are many types of perception, this thesis focuses on the improvement of the visual robotics perception systems. By implementing a broadband passive sensing system in conjunction with current perception algorithms, this thesis explores scene reconstruction and world modeling. The process involves two main steps. The first is stereo correspondence using block matching algorithms with filtering to improve the quality of this matching process. The disparity maps are then transformed into 3D point clouds. These point clouds are filtered again before the registration process is done. The registration uses a SAC-IA matching technique to align the point clouds with minimum error.  The registered final cloud is then filtered again to smooth and down sample the large amount of data. This process was implemented through software architecture that utilizes Qt, OpenCV, and Point Cloud Library. It was tested using a variety of experiments on each of the components of the process.  It shows promise for being able to replace or augment existing UGV perception systems in the future. / Master of Science

Latency is a common issue found in robotics teleoperation that is not currently addressed in simulation. This study examined the effects of latency on operator performance for a robot teleoperation navigation task. Operators used a Logitech gamepad controller to teleoperate a robot through both a simulated environment and real-world environment. Both environments had the same dimensions and provided a path with obstacles the participant had to navigate. Participants performed this navigation task under three latency conditions, zero, low and high. Completion time, number of collisions, NASA-TLX, System Usability Survey, and User Experience survey were collected and participant performance compared for all latency conditions across the simulated and real-world environments. Results indicated a significant difference in participant performance between the simulated and real-world scenarios.

Unmanned ground vehicles (UGV) are being explored for use in military domains. Military UGVs operate in complex off-road environments. Vehicle mobility forecasting plays an important role in understanding how and where a vehicle can operate. Traditional mobility forecasting has been done using an analytical model known as the NATO Reference Mobility Model (NRMM). There has been a push to extend the forecasting capabilities of NRMM by integrating more simulation methods. Simulation enables the repeated testing of UGVs in scenarios that would be difficult or dangerous to study in real world testing. To accurately capture UGV performance in simulation, the operating environment must be accurately modeled. Current widely used methods for generating forested virtual environments rely on random methods. These methods result in forests that can appear to be realistic when visually inspected but lack the appropriate distribution of different sizes of vegetation. The size and distribution of vegetation plays a major role in the ability of a vehicle to operate in a forested environment. Therefore, there is a need for alternative forest generation algorithms that generate more realistic virtual forests. To address this, a novel environment generation model based on forest ecology was implemented. This model accurately captures vegetation growth, disbursement, and competition. Simulated UGV self-driving performance for scenes generated using the ecological model was compared to performance for scenes generated using a widely adopted random model. Resulting speeds across each scene were averaged to predict a speed made good (SMG). Vehicle SMG predictions were made in NRMM using scene descriptions matching each of the random and ecological scenes. Using a continuous vegetation override function in simulation, SMG predictions for both methods were similar to the results of NRMM. However, the predicted speeds for scenes generated with the ecological model were different from the predicted speeds for scenes generated with the random model. When examining the distribution and frequency of different sizes of trees, ecological scenes more closely match the distribution and frequency of trees that are expected for real forested environments suggesting that predictions for speed in ecological scenes better represent potential speeds for real environments.