The purpose of this project is to implement obstacle avoidance algorithms to drive the articulated vehicle autonomously in an unknown environment, which is simulated by AgX Dynamics™ simulation software and controlled by Matlab® programming software. Three driving modes are developed for driving the vehicle (Manual, Semi-autonomous and Autonomous) in this project. Path tracking algorithms and obstacle avoidance algorithms are implemented to navigate the vehicle. A GUI was built and used for the manual driving mode in this project. The semi-autonomous mode checked different cases: change lanes, U-turn, following a line, following a path and figure 8 course. The autonomous mode is implemented to drive the articulated vehicle in an unknown environment with moving to a pose path tracking algorithm and VFH+ obstacle avoidance algorithm. Thus, the simulation model and VFH+ obstacle avoidance algorithm seems to be working fine and still can be improved for the autonomous vehicle. The result of this project showed a good performance of the simulation model. Moreover, this simulation software helps to minimize the cost of the articulated vehicle since all tests are in the simulation rather than in the reality.

Modelling objects and simulating them do not always map to each other, and often requires defining additional information outside the scope of the original model to achieve an accurate simulation. For example: cables in \textit{AGX Dynamics} (a simulation library from Algoryx AB) are entirely defined by its physical parameters (e.g. Young's modulus, stiffness, etc.), radius, and the route through which the cables run. This thesis explores two approaches to closing the gap between the modelling of a cable and the creation of one in AGX Dynamics through evaluating current methods applied to generating a route and radius from a mesh. Two methods are identified as being useful in generating a route for a cable from a mesh: one which is a surface simplification algorithm, creating approximations of models using non-manifold meshes with radii defined at each vertex, and another method which creates a skeleton from a model using the surface's curvature to gradually shrink the model into a zero-volume shape. Both methods are evaluated using two different approaches to measuring the closeness to the original mesh from the results: using the metric introduced in the surface simplification method applied along the route, and measuring the mean distance from each point on the surface to the route. We show a clear advantage in the first method's inherent way of approximating the radius of the model but also its lack of detail. We also demonstrate that the second method produces more detailed skeletons, but in turn has issues with skewed routes which do not follow the original mesh. Both methods have their own advantages and disadvantages and with improvements to both radius calculations or adaptions to the fundamental algorithms, they could provide a great way of creating AGX cables from mesh models.