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Transcript of CSPresoMay2010
Tactile feedback can be added to button presses - increasing typing speeds and reducing errors. Haptic Keyboard 80% of the all data has a Geographic context to it. http://developer.android.com/sdk/index.html HTC Magic GPS Digital Compass Accelerometer Bluetooth Wi-Fi What we do/plan to? http://www.openintents.org/en/node/6 http://code.google.com/p/openintents/wiki/SensorSimulator http://www.testiphone.com/ Thanks and Questions Haptic feedback as a technique for pedestrian navigation stratAG Strategic Research in Advanced Geotechnologies http://www.stratag.ie/ Dr. Adam C. Winstanley Ricky Jacob Postgrad Seminar Series May 2010 Supervisor: But if ANYONE can edit OpenStreetMap – what about quality? Worst case scenario – edited (vandalised) data is used
and a pedestrian is directed incorrectly (and dangerously) * OSM Planet dumps are released weekly
* There is quality checking – bots and humans
which monitor new data, edits, and changes We maintain a local secure copy of the OSM database to avoid the problem of edit vandalism Data Quality? OSM for our local geographic region stored and served from a local database server – direct to our navigation applications
We can periodically update our local copy against the global OSM Planet Dump
In our local copy – we can add extra spatial data to the database – which is specific to our locality (ie classroom door numbers, lecture hall names) http://ciict.cs.nuim.ie/files/location/MaynoothCh.html http://ciict.cs.nuim.ie/files/location/MaynoothEn.html Refereed Original Articles/Peer-reviewed Conference/Meeting Proceedings/Papers Jacob R, Zheng J, Winstanley AC, Ciepluch B, Mooney P (2009) Campus Guidance System for International Conferences Based on OpenStreetMap. Proceedings of 9th International Symposium, W2GIS 2009, Maynooth, Ireland, Springer, Berlin / Heidelberg, German, Volume 5886/2009, pp. 187-198
Jacob R, Zheng J, Winstanley AC, Ciepluch B, Mooney P (2009) A Multi-lingual pedestrian navigation and campus guidance system
using CloudMade API. In Lees, B.G. & Laffan, S.W. (eds), 10th International Conference on GeoComputation, UNSW, Sydney,
Jacob R, Winstanley AC, Mac Aoidh E, Meenagh D, ( 2009) Wiimote as a Navigation tool for Pedestrians. Proceedings of CIICT2009 pp. 23-24.
Shalaik B, Jacob R, Winstanley AC (2010) Integrating Real-time Bus-Tracking with Pedestrian Navigation in a Journey Planning System, GISRUK 2010, UCL, London UK
Ciepluch B, Mooney P, Jacob R, Winstanley AC, (2009) Using OpenStreetMap to deliver location-based environmental information in Ireland SIGSPATIAL Special 1: 17-22, ACM.
Ciepluch B, Jacob R,Mooney P, Corcoran P, Winstanley AC (2010) Using a fully open source approach to working with OpenStreetMap, OSGIS 2010, Nottingham, UK
Zheng J,Chen X, Ciepluch B,Winstanley AC , Mooney P, Jacob R(2010) )Mobile routing services for small towns using cloudmade API and OpenStreetMap, 14th International Symposium on Spatial Data Handling, SDH2010, Hong Kong, China Funded by the Strategic Research Cluster grant (07/SRC/I1168) by Science Foundation Ireland under the National Development Plan Simplify the light recognition by integrating info from sensors and OSM
Partially-sighted user has a mobile device and is willing to use
No red-light running
NOT image processing project.
"Image processing should remain relatively simple" (Pun T, et al, 2007)
Run 'in real time' on a mobile device
Currently small scale - wherever OSM has specific coverage Assumptions/Constraints Future Work Real world testing with participants
Refine the algorithm used to navigate - Including different weather/road conditions to help navigate using appropriate path
Integrate use of sound or voice feedback to the user
Port to c++/java for mobile deployment
Establish if haptic is a possible or feasible way of crossing street assitance
Haptic positioning and navigation in an indoor environment. Footway Tactile paving A tactile paving is a line of different stones on a footway that has an easy to detect surface, often more rough than the surrounding ground. tactile_paving: yes/no Crossing highway: footway
road_type: crossing: island;traffic_signals
Ped-traffic-height: So based on the application requirements, we can make the database richer. Peter Mooney and Błażej Ciepłuch OpenStreetMap data preparation and quality checks. Web interfaces for data visualization. Using simple image processing techniques for traffic signal identification. Padraig Corcoran and Peter Mooney Integrating different types of user feedback for an LBS. Multi-ligual LBS. Jianghua Zheng Intergrate a pedestrian navigation system with a Bus arrival time system. Bashir Shalaik Collaborative Research Department of Computer Science NUI Maynooth http://www.haptimap.org/ HaptiMap Visually Impaired Elderly Lead-Me is a Haptic device which uses pulling or pushing to navigate a user Momo is a Haptic navigation device that is comprised of a GPS module, a digital compass, arduino board, two servo motors and a vibration motor. GentleGuide is a wearable Haptic navigation system which consists of two wrist devices for each wrist and a control device. GentleGuide uses vibrations from these devices to guide the user. File-o-Feel - use simple image processing/machine vision techniques to assist users cross the street at traffic signal crossings. Haptics + Pedestrian Navigation for Visually impaired OpenStreetMap The Free Wiki World Map - on a "smart phone" - navigate the user through physical space (paths, roads, traffic signals) using haptic feedback - take advantage of the ability to make a very precise and spatially rich navigation database with OpenStreetMap - include extra attribute information to include for the application. For ex.: The "Height" of Traffic light post. Multi-modality is useful, allowing transfer of information from the relatively overloaded visual sense to hearing and touch. Location and Navigation using non-visual channels - gestures, tactile/haptic interaction and sound. Key outcome from this presentation Haptic feedback can change the way the visually impaired navigate. The perspective projection camera model (a) Acceleration readings in direction of x-, y-, and z-axis with regard to the body of the mobile phone
(b) The posture of mobile phone is decided by yaw (x ), pitch (y ) and roll (z ). Max Correlation = 0.7652 Max Correlation = 0.9858 Image captured Camera Calibration Result Test results Questions?