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CBWare - Distributed Middleware for Autonomous Ground Vehicles

CBWare - Distributed Middleware for Autonomous Ground Vehicles. Master’s Thesis Defense By Vidhyalakshmi Venkitakrishnan Advisor: Dr. Arun Lakhotia Center for Advanced Computer Studies University of Louisiana at Lafayette October 18, 2006. Presentation Outline.

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CBWare - Distributed Middleware for Autonomous Ground Vehicles

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  1. CBWare - Distributed Middleware for Autonomous Ground Vehicles Master’s Thesis Defense By Vidhyalakshmi Venkitakrishnan Advisor: Dr. Arun Lakhotia Center for Advanced Computer Studies University of Louisiana at Lafayette October 18, 2006

  2. Presentation Outline • Part I - Motivation and Research Contributions • Part II - Background and Related Work • Part III - CBWare and Evaluation Results • Part IV - Conclusions and Future Work

  3. Middleware in AGV’s - Motivation

  4. I. Real-time Information Exchange • Processes are computationally intensive and complex • Need for distributing components on multiple machines to achieve fairness and efficiency • Middleware – Key to information exchange among distributed components

  5. CajunBot

  6. II. Sensor Data Fusion LIDAR (Range, Theta) INS (x, y, z) Global (x, y, z)

  7. Sensor Data Fusion – contd. • LIDAR Queue • INS Queue • Fusing most recent reading from queues – not consistent • Both sources generate data at different frequencies

  8. CajunBot on rough terrain DARPA GC 2005

  9. Sensor Data in Rough Terrain t1

  10. III. Log Server • Need data from processes for post-analysis • Collect data to tune parameters • CajunBot – NQE 2005 • Z spike - wall of obstacles detected from log data

  11. IV. Remote Real-time Monitoring

  12. Why Real-time monitoring? • Visual/graphical views of the world seen by system • Internal states of Obstacle Detection • Visualize live data during field testing • Debug problems with processes in real-time

  13. Research Contributions • Real-time Information Exchange in distributed system • Support for fusion of consistent data • Log server • Real-time monitoring capability

  14. What is Middleware? Layer of software that connects different application components. Supports complex, distributed applications Hides heterogeneity of underlying platforms Middleware Background

  15. Types of Middleware • Publish/Subscribe • Client/Server • Remote Procedure Calls • Other IPC Mechanisms: Shared Memory, Message Queues, UNIX IPC

  16. Publish/Subscribe Model Subscriber subscribes to data Publish/Subscribe Middleware Publisher Subscriber Publisher publishes data Middleware delivers data • Powerful abstraction for distributed systems • Message-based anonymous communication • Publishers and Subscribers are decoupled • Good solution for scalability • Examples: CMU-IPC, NDDS, IBM-Gryphon, Siena

  17. Client/Server Model Client 1 Request Client 3 Server Response Client 2 • Clients send request to the server • Server processes requests and responds back • Clients blocks until response from server

  18. Remote Procedure Calls • Protocol to extend Local Procedure • Involves two independent processes, which may reside on different machines • Caller (Process A on Host A) issues procedure call to Callee (Process B on Host B) with list of argument values • Caller is suspended • Callee executes procedure, returns values to Caller • Caller resumes execution • Examples: Java RMI, CORBA, Microsoft DCOM

  19. Robotic Middlewares • IPT (1996) • Object-oriented, message passing toolkit • Unmanned Ground Vehicle • Client/Server Model • MIRO (2002) • Middleware for Mobile Robots • Based on CORBA • Broker (2005) • IPC Toolkit for Multi-Robot Systems • Works on Publish/Subscribe Model

  20. CBWare Architecture • Works on Publish/Subscribe Model • Two types of Interfaces • CBQueues • CBPackets • Log server • Remote monitoring

  21. Dedicated Logging Machine • Separate Machine – Why? • Hard disk – Most sensitive part of a machine • Bumps – Common reason for hard disk crash/failure • Disk crash – Affects autonomous operations • Provision to log only sample of data to disk

  22. Sampling data for remote monitoring • Why sample data sent over wireless network? • Wireless network cannot handle all the data produced • Onboard network – 1 GB LAN Ethernet switch • Wireless network – 802.11g Wireless • Bandwidth • Ethernet LAN: 1000 Mbps • 802.11g wireless: 54 Mbps

  23. CBQueues • Interprocess communication on a single machine • Interface to read/write messages • Built using POSIX Shared memory

  24. Shared Memory Model • Area of memory shared by multiple processes. • Shared Memory area -indistinguishable to a process from unshared memory Code Code Private data Private data Shared data Shared data

  25. Why Shared Memory Model? • Fastest form of IPC available • Negligible communication overhead • Need to deliver high bandwidth sensor data in a timely manner

  26. CajunBot’s Shared Memory Model • Queues for every message type in shared memory area • Messages in every queue temporally ordered • Crucial for Interpolation support

  27. Single Writer Restriction • Only one writer for each message queue, no limit on the number of readers • Enables temporal ordering of data in distributed queues • Multiple producers for same message type • Separate queue maintained for each producer

  28. Data Fusion and Interpolation • INS • generates data at 100 Hz • Produces data at 10 ms interval • LIDAR • LIDAR generates data at 75 Hz • Scans at 13 ms interval • Most recent INS data may be up to 10 ms old when LIDAR scan is read

  29. Stabilization of sensors • In CajunBot, no stabilization of sensors • Fusing most recent data can give erroneous results • 0.5 degree inaccuracy of angular difference -> 2 feet displacement of global point from correct location • Leverage rough terrain to increase visibility • In vehicles with sensor stabilization, can fuse most recent data • Stabilization dampens rotating movements • Sensors wont experience significantly different orientations in the 10 ms period

  30. CBPackets • Distributed interprocess communication across machines • UDP Broadcast • Support for multiple readers and writers

  31. Why UDP Protocol? • Real-time applications • Deliver messages in time • Small Packet Header overhead • TCP Header = 20 bytes, UDP Header = 8 bytes • For a 20 byte message, compare: 40 bytes Vs 28 bytes Example: Case 1: Message Size = 12 bytes Efficiency using TCP = (12 / 12+20) = 0.37 = 37% Efficiency using UDP = (12/ 12+8) = 0.6 = 60% Case 2: Message Size = 1000 bytes Efficiency using TCP = (1000 / 1000+20) = 0.98 = 98% Efficiency using UDP = (1000 / 1000+8) = 0.992 = 99%

  32. Why UDP Protocol? – contd. • Broadcast/Multicast capabilities • Send messages to all processes at once • Connectionless nature • Useful for remote monitoring • No problems if wireless network fails

  33. Data Marshaling • Why data marshaling? • Distributed System – Machines with heterogeneous architectures/OS follow different byte-ordering, alignment strategies • Data converted to neutral format for transmission over the network • Examples of Data Encoding standards: XDR, NDR, CDR • XDR used by CBWare

  34. XDR Translation Decode data Encode data Receiver Sender XDR Format • Encode: Convert data from native format to XDR format • Decode: Convert data from XDR format to native format • Every message marshaled by CBWare before sending over network

  35. Monitoring Process Status • Processes on multiple machines generate status/warning/error messages • Monitoring messages on each machine • Tedious task when system scales to higher level • Cbmesg: Interface for logging and real-time monitoring of process status information

  36. Replication of Shared Memory • Combination of CBQueues and CBPackets • Subscriber replicates local shared memory • Distribute queues to multiple machines • Easy transfer of programs • Scalability of computational power

  37. CBWare Network Evaluation • CBWare evaluation metrics • End-to-End Latency (msec) • Packet Rate • Bandwidth (bytes/second) • Packet Order • Experimental setup • Dell Poweredge servers • 1 GB Ethernet LAN switch

  38. CBWare Network Evaluation Results • End-to-End Latency • Delays ranging from 0.4 msec to 6 msec depending on packet size • Transmission delay = Packet reception time – Packet sent time

  39. CBWare Network Evaluation Results – contd. • Bandwidth and Packet Rate • Packet Rate = (Bandwidth/Message Size) • Maximum rate ranging from 1200 packets/second to 90 packets/second • Packet order • Measurement based on timestamp • No out of order packets on CBWare network • No network congestion • Network Monitoring Tools used: Ethereal, tcpdump

  40. Conclusion • CBWare – Middleware for Autonomous Ground Vehicle • Publish/Subscribe Model • Distributed Information exchange - Shared Memory and UDP Broadcast • Support for fusion of sensor data • Log server • Sampling for remote real-time monitoring

  41. CBWare’s comparison with other Middlewares

  42. Future Work • Fault tolerance • Compression techniques for larger messages • Port CBWare to other Operating Systems

  43. Questions

  44. Extra slides

  45. Distributed Computing System of CajunBot • Onboard Computing system of CajunBot • Four machines • NTP • Separate networks

  46. Why XDR? • XDR format of data is same on all machines • Any machine can decode data encoded by any machine • Easily add machines with different architectures

  47. Log Control • Remote control of central log server (cb_logd) • TCP Connection • Communication using predefined ASCII Protocol • Three types of control signals • Enable logging data • Disable logging data • Change log directory on log server

  48. CBQueues Utilities • Remove corrupted shared memory: cb_qclean • Clean shared memory area • Read/Write to shared memory: cb_qtest • Testing and debugging problems with shared memory

  49. CBWare’s Publish/Subscribe Components • Publisher: cb_publisher • Handles socket operations • Constructs CBPackets • Marshal data • Broadcast on network • Central Log Server: cb_logd • Logs data received from broadcast network to disk • Runs on separate machine to prevent disk failure affecting autonomous operations • Provision to log only a sample of data to disk • Samples data at prescribed interval and broadcasts data on wireless network for remote monitoring

  50. CBWare’s Publish/Subscribe Components – contd. • Subscriber: cb_subscriber • Runs in two modes • Mode 1: Replicate “shared memory” queues across machines • Mode 2: Real-time monitoring on remote laptop • Easy transfer of programs to multiple machines • Easy scalability of computational power

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