Surface modelling and surface following for robots equipped with range sensors

Christopher Pudney

Research output: ThesisDoctoral Thesis

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The construction of surface models from sensor data is an important part of perceptive robotics. When the sensor data are obtained from fixed sensors the problem of occlusion arises. To overcome occlusion, sensors may be mounted on a robot that moves the sensors over the surface. In this thesis the sensors are single–point range finders. The range finders provide a set of sensor points, that is, the surface points detected by the sensors. The sets of sensor points obtained during the robot’s motion are used to construct a surface model. The surface model is used in turn in the computation of the robot’s motion, so surface modelling is performed on–line, that is, the surface model is constructed incrementally from the sensor points as they are obtained. A planar polyhedral surface model is used that is amenable to incremental surface modelling. The surface model consists of a set of model segments, where a neighbour relation allows model segments to share edges. Also sets of adjacent shared edges may form corner vertices. Techniques are presented for incrementally updating the surface model using sets of sensor points. Various model segment operations are employed to do this: model segments may be merged, fissures in model segment perimeters are filled, and shared edges and corner vertices may be formed. Details of these model segment operations are presented. The robot’s control point is moved over the surface model at a fixed distance. This keeps the sensors around the control point within sensing range of the surface, and keeps the control point from colliding with the surface. The remainder of the robot body is kept from colliding with the surface by using redundant degrees–of–freedom. The goal of surface modelling and surface following is to model as much of the surface as possible. The incomplete parts of the surface model (non–shared edges) indicate where sections of surface that have not been exposed to the robot’s sensors lie. The direction of the robot’s motion is chosen such that the robot’s control point is directed to non–shared edges, and then over the unexposed surface near the edge. These techniques have been implemented and results are presented for a variety of simulated robots combined with real range sensor data.
Original languageEnglish
QualificationDoctor of Philosophy
Publication statusUnpublished - 1994


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