There are many situations for which a feasible nonholonomic motion plan must be generated immediately based on real-time perceptual information. Parametric trajectory representations limit computation because they reduce the search space for solutions (at the cost of potentially introducing suboptimality). The use of any parametric trajectory model converts the optimal control formulation into an equivalent nonlinear programming problem. In this paper, curvature polynomials of arbitrary order are used as the assumed form of solution. Polynomials sacrifice little in terms of spanning the set of feasible controls while permitting an expression of the general solution to the system dynamics in terms of decoupled quadratures. These quadratures are then readily linearized to express the necessary conditions for optimality. Resulting trajectories are convenient to manipulate and execute in vehicle controllers and they can be computed with a straightforward numerical procedure in real time.
utomated guided vehicles (AGVs) have been operating effectively in factories for decades. These vehicles have successfully used strategies of deliberately structuring the environment and adapting the process to the automation. The potential of computer vision technology to increase the intelligence and adaptability of AGVs is largely unexploited in contemporary commercially available vehicles.We developed an infrastructure-free AGV that uses four distinct vision systems. Three of them exploit naturally occurring visual cues instead of relying on infrastructure. When coupled with a highly capable trajectory generation algorithm, the system produces four visual servo controllers that guide the vehicle continuously in several contexts. These contexts range from gross motion in the facility to precision operations for lifting and mating parts racks and removing them from semi-trailers. To our knowledge, this is the first instance of an AGV that has operated successfully in a relevant environment for an extended period of time without relying on any infrastructure.
OverviewThe market for AGVs is the oldest established market for mobile robots. This market is probably valued at over US$900 million today [4], [17]. The largest consumer of AGVs is the automotive industry although many other industries, including warehousing and distribution, paper, printing, textiles, and steel, also use these vehicles. Even large 65 ton material handling vehicles in the shipyards of Rotterdam and Brisbane [2] have been successfully automated.
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