This thesis presents a technique termed Blended Shared Control, whereby a human operator's commands are merged with the commands of an electronic agent in real time to control a manipulator. A four degree-of-freedom hydraulic excavator is used as an application example, and two types of models are presented: a fully dynamic model incorporating the actuator and linkage systems suitable for high-fidelity user studies, and a reduced-order velocity-constrained kinematic model amenable for real-time optimization. Intended operator tasks are estimated with a recursive algorithm; the task is optimized in real time; and a command perturbation is computed which, when summed with the operator command, results in a lower task completion time. Experimental results compare Blended Shared Control to other types of controllers including manual control and haptic feedback. Trials indicate that Blended Shared Control decreases task completion time when compared to manual operation.