1. The Need of Unmanned Systems
Is well recognized to perform tasks that are:
DDD (Dull, Dirty, Dangerous)
Also
Distant
Remote diagnoses,
First Aid,
Tele-Surgery, etc
Micro and nano devices
Tele - Surgery
I am sure that I don’t have to convince about the need of UM systems for DDD or distant tasks, nor about .
Telemedicine Consultation
Tele Virutal Consultation

2. Mixed Initiative Control Methods.
(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
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.

3. The spectrum of control modes.
A telerobot can use:
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.
In a Supervisory Controlled system, the ways how the control is passed between the operator and the machine along the time of the action can be classified as:
traded control - if ….
shared control if…..
strict supervisory control if ….
Solid line= major loops are closed through computer, minor loops through human.

4. The traditional approach to control was:
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.

5. 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.
 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.
Behaviors serve as the basic building blocks for robotic actions.

6. Agent
Asset
Environment
Sense
Learn
Act
Plan
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.

7. 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.

8. 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.

9. 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.

10. Agents are not Objects Differ from Objects
Agents may act inside the robot software to implement behaviors:
Feedback controllers
Control subassemblies
Perform Local Goals/ tasks
Differ from Objects
autonomous, reactive and pro-active
encapsulate some state,
are more than expert systems
are situated in their environment and take action instead of just advising to do so.

11. 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).

12. RCS
Embeds a hierarchy of agents within a hierarchy of organizational units: Intelligent Nodes or RCS_Nodes.

13. RCS_Node Update Plan State Predicted Input Observed Input
Perceived Objects & Events
Commanded Actions (Subgoals)
Commanded Task (Goal)
Plan Evaluation
Plan Results
Situation Evaluation
Value Judgment
Sensory Processing
World Modeling
Behavior Generation
Knowledge Database

14. 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.