Robotic manipulators with kinematic redundancy provide increased flexibility, dexterity, and functionality. However, this redundancy allows the existence of an infinite number of configurations that satisfy a set of task requirements. The motion generation of redundant manipulators is thus a problem of optimization, where the best configuration is chosen from multiple feasible solutions. Although this general problem has been investigated in the current literature, methods for incorporating external loads have not been extensively addressed. To implement general external loads applied to a manipulator, equations of motion are derived using Lagrangian dynamics. Energy consumption is then minimized subject to constraints that model a given task and design. This dissertation proposes a method that, under external load conditions, generates efficient and effective optimum motion to perform a given task, along with the required actuator torque profiles and consumed energy.; This proposed optimization methodology can also be used to generate human motions because the human body is a typical example of redundant systems. The problem of motion planning for redundant manipulators is then transformed into the problem of physics-based dynamic human motion prediction.{09}The metabolic energy expenditure, derived with respect to joint space, is used as the cost function for optimization. Using a digital human model represented by the Denavit-Hartenberg (DH) method, realistic motions are predicted for various tasks in which the human generates different motions according to different external loads. This new feature greatly enhances the capabilities of digital human technology, which is currently limited to kinematic or experiment-based simulations.; Finally, the optimization problem is extended to yield a new method for solving differential-algebraic equations (DAEs). The unknown constraint loads from external and internal sources, as well as the motion and required actuator torques, are determined for a given task. In particular, the method of fictitious joints is introduced to solve for the internal joint constraint forces and moments of a redundant manipulator described in DH representation. The results show optimum external constraint loads and accurate calculation of internal joint constraint loads. The proposed optimization formulation is equivalent to solving DAEs without integration.
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