Cyber-Physical Software Agents

Vincenzo Liberatore

Cyberphysical Systems

 Computing in the physical world  Components – – – Sensors, actuators Controllers Networks V. Liberatore Cyberphysical software 2

Cyberphysical Systems: Examples

        Enables Industrial automation [B

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04] Distributed instrumentation [ACRKN

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03] Unmanned vehicles [

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NB03] Home robotics [NN

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02] Distributed virtual environments [

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CCK05] Power distribution [P05] Building structure control [SLT05] V. Liberatore Cyberphysical software 3

Cyberphysical Systems

 Merge cyber- and physical- worlds – Networked control and tele-epistemology [G01]  Sensor networks – Not necessarily wireless or energy constrained – One component of sense-actuator networks V. Liberatore Cyberphysical software 4

Programming Cyberphysical Systems

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Objectives and Challenges

 Objectives – Remote supervision and programming – Adaptive and evolvable – Security and safety  Challenges: decouple control from – Long-haul network delay, losses – Lack of network Quality-of-Service provisioning – Precise environment modeling V. Liberatore Cyberphysical software 6

Vision (1): Agent-based

 Basic properties – Autonomous,

mobile

– Adaptable, flexible, reactive – Knowledgeable, goal-oriented, learning – – Collaborative Persistent  Agents for cyber-physical systems – Aggregation into task-oriented teams – Evolvable  Re-programmability, reconfiguration, extensibility V. Liberatore Cyberphysical software 7

Vision (2): Supervision

 Coarse-grained high-level – Directions – Troubleshooting – Reprogramming Tele-operation Autonomous systems Supervision V. Liberatore Cyberphysical software 8

Advantages of Supervisory Control

 Utilize autonomous capabilities of robot – Less work for the Supervisor  Makes control with delay feasible – Higher Level commands translated into many smaller ones  Still the same safe robots V. Liberatore Cyberphysical software 9

Achieving Generic Control

 Want the same program to powerfully represent unknown, high level commands – Completely generic GUI – Adapts to commands and attributes of robot  Utilizes a small code stub on the robot – Uses modern day windows controls  Works on robots that communicate IP, regardless of OS and programming V. Liberatore Cyberphysical software 10

This talk

  Progress – Agent-oriented platform   Agent-Communication Dynamically load functionality     Mobility Virtual containment Resource Discovery Experience Future work – Application-oriented middleware – –  E.g., Scheduling of mobility AI (knowledge, planning, learning) Security V. Liberatore Cyberphysical software 12

Agent Communication

 Supervisor invokes robotic functionality – Passes parameters using dynamic GUI  Robot communicates with Supervisor – Returns values for display – Notifies supervisor of properties – Able to ask supervisor for assistance  Priority may cause emergency handling V. Liberatore Cyberphysical software 13

Dynamically Load Functionality

 Currently, robot must be fully represented  Supervisor interacts with Virtual Robot – Middleman we can inject code into – Interfaces provide access to robotic attributes  Ability to add new behavior that uses existent functionality and properties – Added to proxy means that they appear as robotic functionality to supervisor V. Liberatore Cyberphysical software 14

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Dynamically Load Functionality

Believes that the robot it is foo() and bar().

bar() function loaded that calls upstream foo() Cyberphysical software Exposes a function foo() 15

Dynamically Load Functionality

 Powerful ability to “reprogram” robot – Doesn’t require actual robotic modification – Send across canned functionality – Reprogram to deal with unknown environment  May wrap up functionality again and again, abstracting away the lower layers  Applies to multiple-robot scenarios – Dynamically reorganize groups of robots V. Liberatore Cyberphysical software 16

Dynamically Load Functionality

Invokes a bar() command Invokes foo() Invokes more_foo() Invokes yet_foo_again() twice V. Liberatore Executes yet_foo_again() twice Cyberphysical software 17

Resource Discovery

 Plug-and-play – Add new resources on the fly – Example: USB   Plug in a USB camera on a USB port But now we want: on a network, with arbitrary units  Example – Locate a robot on the network V. Liberatore Cyberphysical software 19

    Operations – Discover, Join, Look-up, Use Programming – – Include a library Use functions Fault-tolerance – Leases   Join only last for a certain time period Renew the lease – – Multiple look-up servers JavaSpaces  Distributed shared memory URL: www.jini.org

Jini

V. Liberatore Cyberphysical software Courtesy of Sun Microsystems 20

Middleware

    Between application and transport – Libraries to provide advanced functionality – Hide communication Applications – Resource Discovery – Remote Procedure Calls – – – – Security Interoperability (e.g., since Real-Time Corba) Scheduling, resource management, performance analysis Multicast Software development – – Simpler, faster State-of-the-art functionality Middleware over IP – – Wealth of libraries for IP

Critical advantage of the Internet Protocol

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Agent Mobility

 Mobility – Software component stops execution on host A – Resume execution from same state on host B  Benefits – Adapt to changes of physical topology  E.g., if a unit moves and triggers functionality hand-off – – Anticipate planned disconnections Dynamic re-programmability by agent dispatching V. Liberatore Cyberphysical software 22

Agent teams

Virtual Robots: The Core GUI, interface Thin-legacy layer On-board controllers V. Liberatore Cyberphysical software 26

Hierarchical organization

Relationship: Virtual inclusion Chain of command V. Liberatore Cyberphysical software 27

Virtual Containment

 Analogy – A robotic platoon “contains” individual robot – Not necessarily in terms of ontology  Application – Task-oriented teams – Layering V. Liberatore Cyberphysical software 28

Upstream Communication

 Report state upstream – Sensory data collection  Appeals for assistance – Minimal demands of directions from human or intelligent systems  High-level directions  Triggered only by difficult or unexpected events – Improves safety and reliability V. Liberatore Cyberphysical software 29

Hierarchical organization

Relationship: Virtual inclusion Upstream communication V. Liberatore Cyberphysical software 30

Robot id

Experience

Parameter (range) Go!!!

Methods V. Liberatore Cyberphysical software Task-space: Fluid dynamics 31

Demo

 Objective – Close lever  Operations – – Remote command Robotic manipulator  Procedure – Break complex command (CloseLever) into progressively simpler instructions V. Liberatore multiple invocations of multiple invocations of MoveTo(x,y,z) Cyberphysical software Close lever GoTo(x,y,z) 32

Example

Open/Close   MoveTo  Agent-based software  RPCS Virtual Supervisor V. Liberatore Cyberphysical software 33

Other topics

   Security – – – Encrypt communication Authentication and Authorization Standard Java libraires Fault-tolerance – – Look-up with soft-state Checkpoint in JavaSpaces Advanced functionality with little incremental cost – Demonstrate importance of software re-use with state-of-the-art middleware V. Liberatore Cyberphysical software 34

Related Research

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Play-Back Buffers

 Playback – Smooths out network non-determinism  Playback buffers integrated with – Sampling (adaptive

T

) – Control (expiration times, performance metrics)  Packet losses – Reverts to open loop plant (contingency control) V. Liberatore Cyberphysical software 36

Bandwidth Allocation

  Definition – Multiple sense-and-respond flows – Contention for network bandwidth Desiderata – Stability and performance of control systems  Must account for physics – – – Efficiency and fairness Fully distributed, asynchronous, and scalable Dynamic and self reconfigurable V. Liberatore Cyberphysical software 37

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Problem Formulation

Define a utility fn

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(

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≥

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min  Optimization formulation max s.t.  

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r i i r i

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Conclusions

 Remote supervision of robotic manipulation  Compliant control – Local encapsulation – Gentle, compliant, tolerant to network vagaries  Agent-based software – Hierarchical  Demonstration  Future work: middleware, AI, security V. Liberatore Cyberphysical software 39

To Learn More

http://home.case.edu/~vxl11/NetBots/ [email protected]

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