In industrial problems both the task and environment are often very complex. Local planners are not sufficient and, since tasks often involve changing the environment, global planners are limited by time constraints. This paper adopts the notion that pre-processing of the known environment, in order to generate a roadmap, can significantly improve on-line path planning tasks. The authors present results obtained from an instance of the Ariadne's clew algorithm for path planning problems within the steam generator of a nuclear power plant. An, algorithm is then described which performs further pre-processing on the known environment so that, when the environment changes during on-line planning, a valid, although not necessarily connected, roadmap always exists. This is the first step in a planner that could be used in evolving industrial environments.

Many industrial applications are well suited to nonanthropomorphic pick and place robots. Robotworld is adept at performing vertical assembly operations, which may constitute 60% of all manufacturing operations. Furthermore, nonanthropomorphic robots can achieve higher accuracy than anthropomorphic (six degree of freedom) robots because they can be calibrated to higher precision. In this report we describe calibration techniques for Robotworld modules, simple four degree of freedom (x, y, z, /spl theta/) manipulators. Robotworld modules consist of base which is actuated in (x, y) via Sawyer motors, and a servo-controlled rotating and translating end effector arm, which extends downward from the base. Robotworld modules are implicitly coordinated in x and y (to 0.025 mm) because all the Sawyer motors are actuated with respect to the same platen; therefore, only the axes of rotation and translation of the end effector arm, need to be calibrated. We estimated these axes by localizing a calibration peg using multiple crossbeam sensors. We analyzed the performance of our calibration technique via self validation methods and found that as few as 40 observations provided reasonably high precision (0.025 mm root mean squared error).

A system that automatically plans grasp operations is described. This work has been undertaken in the framework of a project for automatic planning of pick-and-place tasks. The originality of the system comes from the consideration of the strong interdependencies existing between the different planning modules that are involved. It deals explicitly with the interactions between transfer motions, approach motions, the propagation of position uncertainty constraints as well as constraints induced by the local environment of the next step in a pick-and-place context. The approach motion step is based on a motion planner that builds an exact representation of a three-dimensional (x, y, theta ) free configuration space.>

The authors propose a representation of positioning uncertainty for robot manipulation tasks and a method by which it can be propagated through robot programs. The objective is to integrate error propagation and analysis into a task-level programming system in order to produce robust programs. This integration is discussed with reference to an example. The method consists of evaluating progressively the uncertainty through a sequence of actions and maintaining a symbolic trace of computations. When a constraint is violated, the system determines the predominant source of uncertainty in order to guide the planning process.>