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Reference: Hu, Huosheng., (1992). Dynamic planning and real-time control for a mobile robot. DPhil. University of Oxford.Citable link to this page:

 

Dynamic planning and real-time control for a mobile robot

Abstract: A mobile robot becomes more intelligent as its control system is given more capabilities torespond to its environment autonomously. This thesis develops a distributed real-time controlsystem for a mobile robot which is intended to operate autonomously in an industrial environment.It is a unified approach to real-time sensing, planning, and control based on a parallel processingarchitecture.To be fully autonomous, a mobile robot must be able to sense its environment, build or updatemaps, plan and execute actions, and adapt its behaviour to environmental changes. The ability of acontrol system to support these complex tasks in real time is significantly affected by the organisationof information pathways within the architecture. After examining different architectures describedin the literature, a transputer-based architecture is developed to maximise the parallel informationflow from sensing to action to provide minimal delay in responding to a dynamically changingenvironment.Taking account of uncertainty, planning an optimal path is difficult since the internal world modelquickly becomes invalid. To find a solution, dynamic changes in the environment are classified asdifferent types of obstacles that are assumed to appear randomly. Bayes' theorem is applied to buildstatistical models to estimate the mean number unexpected obstacles encountered. This provides afeasible way for the global path planner to update its internal world model dynamically based onavailable sensor information. A dynamic programming algorithm is used to plan an optimal path.An array of sonar sensors is used to detect dynamic changes in the environment. To reduceuncertainty in noisy data, a probabilistic sensor model and rule-based heuristics are built. Thecollision avoidance problem is formulated using decision theory to achieve both collision-free andoptimal solution. An optimal decision rule to avoid unexpected obstacles is calculated to minimisethe Bayes risk in trading between a careful maneuver and an alternative path.To control the motion of the robot to follow the planned path, a new guidance system is proposedto provide dynamic trajectory planning and optimal tracking capability to a mobile robot that issubject to nonholonomic kinematic constraints.The success of this approach is demonstrated by the Turtle mobile robot which is able to interactintelligently with a dynamically changing environment.

Type of Award:DPhil Level of Award:Doctoral Awarding Institution: University of Oxford Notes:The digital copy of this thesis has been made available thanks to the generosity of Dr Leonard Polonsky

Contributors

Brady, MichaelMore by this contributor

RoleSupervisor

 

Prof. Mike BradyMore by this contributor

RoleSupervisor

 Bibliographic Details

Issue Date: 1992Identifiers

Urn: uuid:abe96c99-4b82-492b-8e38-40d0f7748187

Source identifier: 603849210 Item Description

Type: Thesis;

Language: eng Subjects: Mobile robots Real-time control Tiny URL: td:603849210

Relationships





Autor: Hu, Huosheng. - institutionUniversity of Oxford facultyMathematical and Physical Sciences Division - - - - Contributors Brady, Mi

Fuente: https://ora.ox.ac.uk/objects/uuid:abe96c99-4b82-492b-8e38-40d0f7748187



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