Structured Control for Autonomous Robots

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Structured Control for Autonomous Robots

• Reid G. Simmons
• Carnegie Mellon University
• Uday Rajanna

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• Task Control Architecture
• 1) Layering reactive behaviours onto
  deliberative components
• 2) It is a structured control approach where the
  deliberative components handle normal
  situations and the reactive behaviours handle
  exceptional situations.
• 3) TCA control constructs facilitates modular
  and evolutionary system development.

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• Task Control refers to the problem of
  coordinating perceptual, planning and execution
  components of a robot system to achieve a given
  set of goals
• Behaviour Based Systems
• As the number of behaviours and the degree of
  interaction between them grows, it becomes
  increasingly difficult to design good arbitration
  schemes of which behaviour takes a higher or
  lower priority of execution.

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• TCA Control Constructs
• 1) Distributed inter-process communication
• 2) Task decomposition and temporal constraints
• between subtasks.
• 3) Resource allocation and management.
• 4) Execution monitoring
• 5) Exception handling.
• TCA class of messages
• 1) Inform
• 2) Query
• 3) Goal
• 4) Command
• 5) Monitor
• 6) Exception

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• Ambler walking system
• 1) Central Control
• 2) Gait Planner
• 3) Footfall planner
• 4) Leg recovery planner
• 5) Error recovery planner
• 6) Scanner Interface
• 7) Image Queue manager
• 8) Local terrain mapper
• 9) Message routing table
• 10) Resource Schedules
• 11) Task Trees
• 12) Real time controller

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• TCA provides mechanisms for
• Deliberation
• Uses a task tree that keeps the overall
  process in mind. Constraints like delay
  planning, handling intervals, achievement
  interval, goal
• interval are used.
• Reactivity
• Uses task trees which are reactive in nature
  in conjunction with the deliberation scheme
  to account for sudden changes in environment
  and exception errors.
• TCA also allows for incremental development of
  the system with minimal impact to the existing
  architecture.
• TCA module utilization was improved to be very
  concurrent by the addition of DP between Take
  Steps node and the node directly preceding its
  parent.

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• Conclusions
• 1) TCA provides a framework for developing and
  controlling autonomous robots
• 2) The control of planning, perception and action
  must be well structured for general purpose
  robots to succeed in rich and uncertain
  environments.
• 3) TCA supports both deliberative and reactive
  architectures with the side coming into play
  in case of exceptions and changes in
  environments.
• 4) Use of constraints provides a basis for
  analysing interactions between behaviours.
• 5) Using formal methods to analyse constraints on
  behaviour would greatly facilitate
  development of robot systems.
• 6) Incremental addition of new modules can be
  performed.