Motor Schema Based Navigation for a Mobile Robot: An Approach to Programming by Behavior Ronald C. Arkin Reviewed By: Chris Miles.

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Presentation transcript:

Motor Schema Based Navigation for a Mobile Robot: An Approach to Programming by Behavior Ronald C. Arkin Reviewed By: Chris Miles

Goal The usual Effective navigation through complex areas

Motivation for Technique Rigid Hard Coding – Bad Hybrid behavior based system – Good

Schemas “A generic specification of a computing agent” A schema is a specific processing unit Each implements a particular behavior Outputs –Desired Velocity Vector –Inputs to other schemas

Instantiation In contrast to most systems schemas are designed to be instantiated many times. Schemas have very specific tasks – Avoid a single object Parameterized – What to avoid, where to head For each individual task the planner wants the robot to accomplish, it instantiates a schema

Arbitration - Potential Fields Schema Instantiations produce velocity vectors These goals are arbitrated through addition Summing the vectors produces the usual potential field maps This gives robustness, and fast processing with a large number of schema

Communication Schema communicate to overcome deadlocks Example: A path following schema will temporarily disable itself if it senses the robot has come to a deadlock. This communication occurs through a blackboard system

Hybridization The schema system forms the reactive layer in a hybrid system. The planning system is dealt with through the AuRA planner – In itself a hierarchical system.

AuRA Planning Mission Planner –Determines Destinations Navigator –Constructs waypoints between these destinations – Uses a priori navigation graph Pilot –Instantiates Schemas to reach waypoints

Vision Based Obstacle Avoidance A schema monitors a camera attached to the robot If it detects a possible obstacle it instantiates two schemas 1.Tracks the obstacle – outputting its confidence in its existence 2.Takes the confidence in and location of the obstacle and avoids it

Results In a simulated environment a robot can avoid static circular obstacles They have excellent ideas and outlines of what they will do in this paper, but there results show only that potential fields is an effective arbitration technique

Quote “The obstacle is first grown in a configure space manner to enable the robot to be treated henceforth as a point for path planning purposes”.