The International Journal of Robotics Research · 1986 · 252 citations · 15 references
EngineeringField RoboticsPlanning ProcessTask PlanningTrajectory PlanningUncertainty QuantificationSystems EngineeringGoal StatesRobot LearningKinematicsComputational GeometryConfiguration SpaceHealth SciencesGeometric ModelingPath PlanningDesignComputer SciencePlanning TheoryFine Motion PlanningAi PlanningMotion PlanningAutomationPlanningRobotics
This paper outlines a method for planning motions in the presence of uncertainty. Tasks are modeled as geometrical goals in configuration space. The planning process consists of determining regions from which particular motions are guar anteed to reach a desired goal successfully. An algorithm is presented for backprojecting from desired goal states. The backprojection regions are computed by erecting constraints that geometrically capture the uncertainty in motion. The relationship of backprojections to goal recognizability is discussed within the formal framework of preimages. This relationship suggests a partitioning of desired goal states into recognizable goal states. Backprojections are actually per formed from this partitioning.
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Spatial Planning: A Configuration Space Approach
Tomás Lozano‐Pérez · IEEE Transactions on Computers · 1983 · 2.1K citations