Throughout a ground vehicle development program, it is necessary to possess the loads the vehicle will experience. Unfortunately, actual loads are only available at the conclusion of the program, when the vehicle has been built and design changes are costly. The design engineer is challenged with using predicted loads early in the design process, when changes are relatively easy and inexpensive to make. It is advantageous, therefore, to accurately predict these loads early in the program, thus improving the vehicle design and, ultimately, saving time and money. The prediction of these loads depends on the fidelity of the vehicle models and their excitation. The focus of this thesis is the development of techniques for using 3D terrain surface measurements for vehicular simulations. Contributions are made to vehicle model parameter identification, terrain filtering, and application-dependent interpolation methods for 3D terrain surfaces. Modeling and simulation are used to improve and shorten a vehicle's development cycle, thus, saving time and money. An important aspect in developing a vehicle model is to identify the parameters. Some parameters are easily measured with readily available tools; however, other parameters require dismantling the vehicle or using expensive test equipment. Initial estimates of these difficult or costly to obtain parameters are made based on similar vehicle models or standard practices. In this work, a parameter identification method is presented to obtain a better estimate of these inaccessible parameters using measured terrain excitations. By knowing the excitations to the physical vehicle, the simulated response can be compared to measured response, and then the vehicle model's parameters can be optimized such that the error between the responses is minimized. Through this process, better estimates of the vehicle's parameter are obtained, which demonstrates that measured terrain can improve vehicle development by increasing the accuracy of parameter estimates. The principal excitation to any ground vehicle is the terrain, and by obtaining more accurate representations of the terrain, vehicular simulation techniques are advanced. Many simple vehicle models use a point contact tire model, which performs poorly when short wavelength irregularities are present because the model neglects the tire's mechanical filtering properties. Therefore, a filter is used to emulate a tire's mechanical filtering mechanism and create an effective terrain profile. In this work, terrain filters are evaluated to quantify their effect on the sprung mass response of the dynamic simulation of a seven degree of freedom vehicle model. In any vehicular simulation, there is a balance between analytical expense and simulation realism. This balance often limits simulations to 2D terrain profile excitations, but as computing power increases the computational expense decreases. Thus, 3D terrain excitations for vehicular simulation are a tool for advancing simulation realism that is becoming less computationally expensive. Three dimensional terrain surfaces are measured with a non-uniform spacing in the horizontal plane; therefore, application-dependent gridding methods are developed in this work to interpolate 3D terrain surface to uniform grid spacing. The uniform grid spacing allows 3D terrain surfaces to be used more efficiently in any vehicular simulation when compared to non-uniform spacing. / Master of Science

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The world is slowly moving into increased human-robot interaction where both humans and robots can co-exist in the same domain. For the robot to be able to operate effectively in a man’s designed environment, it becomes necessary to model the robot with human capabilities as humans are seen as more capable. Replicating human becomes a huge challenge due to numerous degrees-of-freedom (DOFs) that human possess resulting into too many variables and nonlinear equations. Other challenges do occur like singularities.   In this thesis, the singularity challenge of a redundant humanoid arm is explored while maintaining a simple 7 DOF serial chain structure. As opposed to the 30 DOF human arm, a simpler 7 DOF humanoid arm is adopted and studied to eliminate the singularity challenges. The singularity problem mainly comes from the elbow and the spherical joints at the shoulder and wrist. A step-by-step review of available inverse kinematics techniques is made with more focus on the iterative Jacobian-based methods. A step-by-step approach is adopted so as to identify the source of singularities while using the iterative Jacobian-based techniques that are able to handle the nonlinearities of the equations.   The Singular Value Filtering (SVF) technique coupled with Selectively Damped Least Squares (SDLS) is employed. Without any restrictions to the stretch of the arm or end-effector pose, the method demonstrates, in conjunction with Euler angle singularity avoidance method, the elimination of singularity problems. This is achieved with no adjustment to kinematic model of the manipulator.