| An algorithm is presented for
wheeled mobile robot trajectory generation that achieves a high degree of
generality and efficiency. The generality derives from numerical linearization
and inversion of forward models of propulsion, suspension, and motion for
any type of vehicle. Efficiency is achieved by using fast numerical optimization
techniques and effective initial guesses for the vehicle controls parameters.
This approach can accommodate such effects as rough terrain, vehicle dynamics,
models of wheel-terrain interaction, and other effects of interest. It can
accommodate boundary and internal constraints while optimizing an objective
function that might, for example, involve such criteria as obstacle avoidance,
cost, risk, time, or energy consumption in any combination. The algorithm
is efficient enough to use in real time due to its use of nonlinear programming
techniques that involve searching the space of parameterized vehicle controls.
Applications of the presented methods are demonstrated for planetary rovers.
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