The Need of Unmanned Systems

• DDD (Dull, Dirty, Dangerous)• Also

– Distant • Remote diagnoses,

• First Aid,

• Tele-Surgery, etc

– Micro and nano devices

Is well recognized to perform tasks that are:

Telemedicine Consultation

Tele - Surgery

Tele Virutal Consultation

• (Manual) Remote Control:– needs line of sight (LOS) between HO and machine.

– all control loops closed through the HO.

– needs full attention from the HO.

• Teleoperated: – no need of LOS– few sensors to enable HO decision making process

– needs full attention from the HO.

• Human Supervisory Control: – sensors used to enable autonomous decisions.

– only partial attention from the HO is needed.

• Autonomous tasks:– tasks performed based on sensory information.

– HO monitors and communicates information about goals, constraints, plans, etc.

Mixed Initiative Control Methods.

The spectrum of control modes.

Solid line= major loops are closed through computer, minor loops through human.

• traded control: control is or at operator or at the autonomous sub-system.

• shared control: the instructions given by HO and by the robot are combined.

• strict supervisory control: the HO instructs the robot, then observes its autonomous actions.

A telerobot can use:

System Decomposition

• The traditional approach to control was: the Sense-Plan-Act (SPA) approach

inherently sequential

This produces deliberative architectures. Behavior Based Architectures produce

inherently parallel systems.

Make the machine an agent in human operator’s service.

What is a behavior?

• An individual behavior is a stimulus/ response pair for a given environmental setting that is modulated by attention and determined by intention.

• Behaviors serve as the basic building blocks for robotic actions.

Attention: prioritizes tasks and focuses sensory resources and is determined by the current environmental context.

Intention: determines which set of behaviors should be active based on the robotic agent’s internal goals and objectives.

Apparent or emergent behavior: the global behavior of the robot as a consequence of the interaction of the active individual behaviors.

Environment

Sense Asset

Learn

PlanAct

Agent

• An agency relationship is present whenever one party (the principle) depends on another party (the agent) to undertake some task on the principle’s behalf.

• An agent is an entity which can be viewed as perceiving its environment through sensors and acting upon that environment through effectors.

Assembling Behaviors.

• Systems are constructed from multiple behaviors.

• Emergent behavior implies a holistic (attention to the “whole”) capability where the sum is considerably greater than its parts.

• Emergence is “the appearance of novel properties in whole systems”.

• Intelligence emerges from the interaction of the components of the system.

• Coordination functions are algorithms used to assemble behaviors.– Conflict can result when two or more behaviors are active, each

with its own independent response.

The Agent

• An agent is a computer system capable of autonomous action in some environments.

• A general way in which the term agent is used is to denote a hardware or software-based computer system that enjoys the following properties: – autonomy: agents operate without the direct intervention of

humans or others, and have some kind of control over their actions and internal state;

– social ability: agents interact with other agents (and possibly humans) via some kind of agent-communication language;

– reactivity: agents perceive their environment, (which may be the physical world, a user via a graphical user interface, or a collection of other agents), and respond in a timely fashion to changes that occur in it;

– pro-activeness: agents do not simply act in response to their environment; they are able to exhibit goal-directed behavior by taking the initiative.

Agents and Behaviors

• Behavior is defined as the way how we/people observe the system/robot acts/behaves.

• The robot system is NOT aware of what we know about it.– What makes the system act as we observe is its

software.

• Agents are implementing behaviors.

Agent control loop

• agent starts in some initial internal state i0 .

• observes its environment state e, and generates a percept see(e).

• internal state of the agent is then updated via next function, becoming next_(i0, see(e)).

• the action selected by agent is action (next(i0, see(e))))

This action is then performed.

• Goto (2).

RCSEmbeds a hierarchy of agents within a hierarchy of organizational units: Intelligent Nodes or RCS_Nodes.

RCS_Node

Value Judgment

Sensory Processing

World Modeling

Behavior Generation

Knowledge Database

Update Plan

StatePredicted Input

Observed Input

Perceived Objects &

Events

Commanded Actions

(Subgoals)

Commanded Task (Goal)Plan

EvaluationPla

n R

esul

tsS

ituation E

valuation

Sequential and Parallel Task Decompositions.

• Sense Plan Architectures use a functional decomposition, i.e., – the systems consist of sequential modules achieving independent

functions (sense-world, generate-plan, translate-plan-into-actions).

• RCS architecture advocates decomposition along a temporal dimension.

• The Reactive Architectures in general, use a task-oriented decomposition, i.e.,

– the systems consist of parallel (concurrently executed) modules achieving specific tasks (avoid-obstacle, follow-wall, etc.)

– implemented with situated automata model.

• It recognizes a fundamental relationship an agent has as a participant within its environment.• Principles of reactivity are hybridized in circuits, which corresponds with robots goals and intentions.