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We present a mathematical programming-based method for optimal control of discrete-time nonlinear systems subject to temporal logic task specifications. We use linear temporal logic (LTL) to specify a wide range of properties and tasks, such as safety, progress, response, surveillance, repeated assembly, and environmental monitoring. Our method directly encodes an LTL formula as mixed-integer linear constraints on the continuous system variables, avoiding the computationally expensive processes of creating a finite abstraction of the system and a Bu ̈chi automaton for the specification. In numerical experiments, we solve temporal logic motion planning tasks for high-dimensional (more than 10 continuous states) dynamical systems.