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Christian Mandel Bernd Krieg-Brckner Bernd Gersdorf Christoph Budelmann Marcus-Sebastian Schrder Navigation Aid for Mobility Assistants Joint CEWIT-TZI-acatech Workshop ICT meets Medicine and Health ICTMH 2013

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Compensate declining physical and cognitive capabilities Provide navigation assistance that considers specific needs: Precise localization Route planning respecting vehicle specific constraints User interface suitable for the elderly Overview: Walker with NavigationAid IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Two versions of OdoWheel Inertial Measurement Unit (IMU) Current revision comprises 3-axis acceleration sensor and gyrometer Bluetooth [Low energy] radio link Battery [solar] driven power supply 32 bit microcontroller Extended Kalman Filter fuses accelerometer- and gyro-data Odometry Additional Hardware Component: OdoWheel IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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OSM description of road network, land usage, buildings, Open community project Based on user-recorded GPS track logs, or vectorization of aerial images XML vector representation with atomic building blocks: points, ways, relations Free tagging system for annotation of properties Handy modeling tools such as the Java-OpenStreetMap-Editor (JOSM) Environment Representation: OpenStreetMap (OSM) IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Environment Representation: OpenStreetMap (OSM) Road network stored in PMR-Quadtree Space partitioning data structure sorting its entries into buckets Bucket is split into four child buckets when |entries| exceeds threshold c Let N := |position hypotheses| and M:= |road segments| O(c*N) instead of O(M*N) distance(road segment, position) queries for finding closest road segment to given pose hypothesis when using PMR-Quadtree [1] E.G. Hoel and H. Samet: Efficient Processing of Spatial Queries in Line Segment Databases. In: Advances in Spatial Databases; Vol.: 525 of Lecture Notes in Computer Science, pages 237-256. Springer Verlag, 1991. IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Monte Carlo Localization: Motivation [2] GPS Essentials of Satellite Navigation Compendium. uBlox, 2009. Online: http://www.u-blox.ch/images/downloads/Product_Docs/GPS_Compendium%28GPS-X-02007%29.pdf Sources of GPS errors Multipath signals reflected from buildings, trees, mountains, IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Monte Carlo Localization: Overview Motion Update Sensor Update Resampling Model estimate of current position by set of samples Move each pose hypothesis according to: Odometry measurements Translational, and rotational noise IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Monte Carlo Localization: Overview Motion Update Sensor Update Resampling Score each pose hypothesis according to: Distance to GPS measurement Distance to closest OSM path Type of closest OSM path, kind of entity passed over during last motion update IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Monte Carlo Localization: Overview Motion Update Sensor Update Resampling Rebuild set of samples for next frame Samples score determines probability to occur in the new set IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Estimated state is a pose in 2-D Particle implementation: Motion model: State transition based on traveled distance and rotation Update of sample position Monte Carlo Localization: Motion Update IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Monte Carlo Localization: Sensor Update Sensor model: position measurement from a connected GPS device virtual path distance measurement (always zero) virtual measurement describing expected behavior Computation of weighting: IntroductionOutdoor LocalizationPath PlanningUser InterfaceResults / Outlook

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IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook OSM Based Route Planning Uses 22 different path types including oneway paths Platform/user-sepcific weighting Uses A-star algorithm Computation of turn advices

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Map View of User Interface detailed representation of surroundings immediate walking direction abstract path network with walking directionplanned path current position IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Compass View of User Interface abstract path network with walking direction immediate walking direction IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Selecting (special) Targets in User Interface push to speak target location type in target location push to select special target IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Localization Example Estimated trajectory (red) vs. GPS trajectory (green) IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Future Work Outdoor Localizer Route Planning Evaluation Hardware Integration Vehicle Platforms Barthel Index NASA Task Load Index IntroductionOutdoor LocalizationRoute PlanningUser InterfaceResults / Outlook

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Navigation Aid for Mobility Assistants Joint CEWIT-TZI-acatech Workshop ICT meets Medicine and Health ICTMH 2013 Thank you for your attention! Questions?