AuRA: Principles and Practice in Review Paper by

AuRA: Principles and Practice in Review

• Paper by:

• Ronald C. Arkin and Tucker Balch

• Present By:

• Jirakhom Ruttanavakul

AuRA : Autonomous Robot Architecture

• AuRA : Autonomous Robot Architecture

• AuRA : was developed in mid-1980’s (as a hybrid approach to robotic navigation)

• Arose from

• A deliberative or hierarchical planner
• A reactive controller

The structure of AuRA

• The structure of AuRA

• The strengths of AuRA

• The origin of AuRA Theory

• The example of AuRA-Based System

• Conclusion

Mission Planner: Establishing high-level goals and constraints within which it must operate.

• Mission Planner: Establishing high-level goals and constraints within which it must operate.

• Spatial Reasoner: Using the knowledge in long-term memory to construct a sequence of path legs.

• Plan Sequencer: Translating each path legs into a set of motor behaviors (schemas)

• The schemas will be sent to the robot.

• The deliberative system will stop and reactive system will start.

Schema Manage: Controlling and Monitoring the behavioral processes at run-time.

• Schema Manage: Controlling and Monitoring the behavioral processes at run-time.

• Motor Schema associated with Perceptual schema: Providing the stimulus required for that particular behavior.

• Homeostatic Control System: Maintaining balance and system equilibrium.

• Hierarchical Component will be reactivated, only if a failure is detected (lack of progress, velocity of zero, and timeout)

Modularity: Components can be replaced with others in straightforward manner

• Modularity: Components can be replaced with others in straightforward manner

• Flexibility: It provides for introducing adaptation and learning methods.

• Generalizability:

• Hybridization: Gat’s Atlantis Architecture, 3T

Aura : influenced by a wide range of ethological, neuroscientific, and psychological study

• Aura : influenced by a wide range of ethological, neuroscientific, and psychological study

• Schema Theory: a theory of intelligence which represents motor and perceptual control at a level of abstraction higher than that of neural networks. The AuRA employs at the reactive control level, encoded using an analog of the potential fields method

• Justification for hybridization of reactive and deliberative control: found in studies by psychologists

• Homeostatic Control System: developed using models of the mammalian endocrine system as inspiration.

Trash-Collecting Robots : Built by a Group of Georgia Tech Student in 1994

• Trash-Collecting Robots : Built by a Group of Georgia Tech Student in 1994

• Objective : Searching for trash, Picking it up, & Carrying it to the wastebaskets

• The trash : consisting of Styrofoam coffee cups, wads of paper, and soda cans.

• The environment : consisting of obstacles such as tables and chairs.

Power System & Computer Equipment

• Power System & Computer Equipment

• Sensors : including bumper switches for collision detection

• Color Video Camera : The key factor of the robots’ success in their task

• A custom-built gripper : attatched to the front of the robots

• Infrared Sensor : mounted in the gripper

The lowest level : motor schemas

• The lowest level : motor schemas

• Schema Controller instantiates and runs schemas as directed by the Plan Sequencer.

• A set of schemas is active at a time

• Each motor schemas : Computing a vector which indicates a desired direction of motion.

• The vector is combine to generate the overall movement vector

• The overall movement : sent to the robot’s actuator

Detect-red-blob : using vision to find the location of the goal (red is trash, blue for wastebaskets, green for robots).

• Detect-red-blob : using vision to find the location of the goal (red is trash, blue for wastebaskets, green for robots).

• Detect-obstacles : using bumper switches to detects and tracks obstacles

• Move-to-goal : generating a vector towards the goal found by detect-red-blob

• Avoid-static-obstacles : generating a vector away from any detected obstacles

• Detect-IR-beam-broken: used as the trigger to close the gripper around the object

The plan, coded by humans, is a sequence of behavioral assemblages and perceptual triggers which causes the transition between them, expressed as a Finite State Acceptor (FSA)

• The plan, coded by humans, is a sequence of behavioral assemblages and perceptual triggers which causes the transition between them, expressed as a Finite State Acceptor (FSA)

• States : identified with circles

• Perceptual Triggers : directed arcs between states

• When the condition on arcs is met, the state will be changed

No communication devices with the robots

• No communication devices with the robots

• Simply paint the robots to green color.

• The robot move away from the green in wander-for-trash state

The AuRA is a hybrid architecture which combine deliberative planner, based on traditional AI techniques and reactive controller, based on schema theory.

• The AuRA is a hybrid architecture which combine deliberative planner, based on traditional AI techniques and reactive controller, based on schema theory.

Thank You

• Thank You

• Questions & Comments