Databases for Robotics Applications

1. Databases for Robotics Applications Thomas Young

2. Presentation Outline • Introduction • Database Solutions • Spatio Temporal Databases • TinyDB

3. Introduction Various types of Database Applications • Bipedal Robot Research • Obstacle Database • Sensor Networks • Moving Objects Database

4. Bipedal Robot Research Training a bipedal robot to walk

5. Bipedal Robot Research

6. Bipedal Robot Research Components • Servo Motors • Sensors • PD Motor Control • Neural Net • Database

7. Bipedal Robot Research Learning Process

8. Obstacle Database • Database of natural obstacles • CFIT Problem in Aviation • Terrain Awareness System

9. Obstacle Database

10. Obstacle Database • eTAWS • Database of man made obstacles including bridges, towers, overpasses, hydro lines, buildings

11. Obstacle Database • Standard relational database • Spatial representations stored as vectors or rasters using an extended spatial type • Uses SQL queries

12. Sensor Networks • Networks of either homogeneous or heterogenous sensor types • Sensors characterized by power, computation, communications • Networks characterized by configuration, types of sensors • Harvard Motes • Smart Dust

13. Sensor Networks Homogeneous Sensor Network

14. Moving Objects Database • Database of objects that change position in time and space • Tracking of vehicles, assets, people, animals • Fleet tracking • Scientific research • Surveillance

15. Moving Objects Database Vehicular Traffic

16. Moving Objects Database Firefighting Assets

17. Moving Objects Database Ground Forces

18. Database Solutions • NOSQL • TinyDB • Spatio Temporal Databases

19. NOSQL • No ACID guarantee • Distributed fault tolerant architecture • Do not follow a fixed schema • Performance and scalability

20. TinyDB • Sensor Networks with nodes running TinyOS • Runs TinySQL (subset of SQL) • Extensible framework for attributes, commands, and aggregates • Interacts with sensor network as a whole • Multiple concurrent queries • Entire sensor network is infinitely long table • Tuples consist of individual sensor and attributes

21. TinyDB Energy Cost of a query that selects 100 tuples is less than the cost of a single packet transmission

22. Spatio Temporal Databases • Objects that move in space and time • Handle queries that index by an object, time or time interval, physical location

23. Spatio Temporal Databases Query Examples • Find all objects in a given area at a given time • Find all objects in a given area between these times • Find which object was closest to position X at time T • How many objects passed through area A at time T • Given spatio-temporal relationships R1 and R2, find out which pairs intersected between T1 and T2

24. Spatio Temporal Databases R Trees

25. Spatio Temporal Databases Historical R Tree

26. Spatio Temporal Databases • How to store “now”? Use a large value… • Long lived objects will have very long MBRs, difficult to cluster • Extensive overlap and empty space  bad query performance for specific queries • Use partiallly persistent R-tree • Multi-version Binary Tree applied to R-tree

27. Spatio Temporal Databases Trees at consecutive timestamps may share branches to save space

28. Spatio Temporal Databases Trees at consecutive timestamps may share branches to save space.

29. Spatio Temporal Databases HR-trees answer timestamp queries very efficiently. • A timestamp query degenerates into a spatial window query handled by the corresponding R-tree at the query timestamp. Not quite efficient: • Expensive space consumption. • A node needs to be duplicated even when only one object moves. • Interval query processing is inefficient. • Although redundancy (from duplication) is necessary to maintain good timestamp query performance, it is excessive in HR-trees

30. Spatio Temporal Databases • What if you want to track only one object? • Use artificial deletes to get rid of others • Approximate the object using many small MBRs • This uses more space • Instead split the areas into minimum number of MBRs that contain the objects that move the most • If object has constant velocity then equidistant splits • Given x splits the best splits can be determined in O(xlogn) time

31. THE END THANK YOU

32. References • TinyDB Design Code and Implementations, Prakash Achutaramaiah • Implementation and Research Issues in Query Processing for Wireless Sensor Networks, Wei Hong, Sam Madden • An On-Line Biped Mini-Robot Motion Learning Using Neural Network and Database Management, Shih Fen Cheng, 2011 Seventh International Conference on Natural Computing • Towards Sensor Database Systems, Bonnet Phillipe, Gehrke Johannes, Seshadri Praveen • Distributed Sensor Databases for Multi-robot Teams, Cowley Anthony, Hwa-Chow Hsu, Camillo J, Taylor • Future Robotics Database Management System Alonw With Cloud TPS, Vijaykumar S, Sarvanakumar S G, International Journal on Cloud Computing: Services and Architecture (IJCCSA), Vol 1, No.3, Novermber 2011 • [Tao & Papadias 01]:MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries. VLDB 2001: 431-440