American robotics

Robots of the United States include simple household robots such as Roomba, the most successful consumer robot in history, to sophisticated autonomous aircraft such as the MQ-9 Reaper that cost 18 million dollars per unit. The first industrial robot, robot company, and exoskeletons as well as the first dynamically balancing, organic, and nanoscale robots originate from the United States

Three Laws of Robotics

In science fiction, the Three Laws of Robotics are a set of three rules written, which almost all positronic robots appearing in his fiction must obey. Introduced in his 1942 short story "Runaround", although foreshadowed in a few earlier stories, the Laws state the following

"A robot may not injure a human being or, through inaction, allow a human being to come to harm.
A robot must obey any orders given to it by human beings, except where such orders would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with the First or Second Law. "

Mobile manipulator

Mobile manipulator is nowadays a widespread term to refer to robot systems built from a robotic manipulator arm mounted on a mobile platform. Such systems combine the advantages of mobile platforms and robotic manipulator arms and reduce their drawbacks. For instance, the mobile platform extends the workspace of the arm, whereas an arm offers several operational functionalities.
A mobile manipulation system offers a dual advantage of mobility offered by a mobile platform and dexterity offered by the manipulator. The mobile platform offers unlimited workspace to the manipulator. The extra degrees of freedom of the mobile platform also provide user with more choices. However the operation of such a system is challenging because of the many degrees of freedom and the unstructured environment that it performs in.

At the moment mobile manipulation is a subject of major focus in development and research environments, and mobile manipulators, either autonomous or teleoperated, are used in many different areas, e.g. space exploration, military operations, home-care and health-care. However, within the industrial field the implementation of mobile manipulators has been limited, although the needs for intelligent and flexible automation are present. In addition, the necessary technology entities (mobile platforms, robot manipulators, ) are, to a large extent, available off-the-shelf components.
A reason for this is that the manufacturing industries act traditionally and, therefore, have reluctance in taking risks by implementing new technologies. Also within the field of industrial mobile manipulation the centre of attention has been on optimization of the individual technologies, especially robot manipulators and tooling , while the integration, use and application have been neglected. This means that few implementations of mobile robots, in production environments, have been reported

Webots

Webots is a professional robot simulator widely used for educational purposes. The Webots project started in 1996, initially developed by Dr. Olivier Michel at the Swiss Federal Institute of Technology in Lausanne, Switzerland.
Webots uses the ODE for detecting of collisions and simulating rigid body dynamics. The ODE library allows one to accurately simulate physical properties of objects such as velocity, inertia and friction.
A large collection of freely modifiable robot models comes in the software distribution. In addition, it is also possible to build new models from scratch. When designing a robot model, the user specifies both the graphical and the physical properties of the objects. The graphical properties include the shape, dimensions, position and orientation, colors, and texture of the object. The physical properties include the mass, friction factor, as well as the spring and damping constants.
Webots includes a set of sensors and actuators frequently used in robotic experiments, e.g. proximity sensors, light sensors, touch sensors, GPS, accelerometers, cameras, emitters and receivers, servo motors (rotational & linear), position and force sensor, LEDs, grippers, gyros and compass

Robotics suites

A robotics suite is a visual environment for robot control and simulation. They are typically an end-to-end platform for robotics development and include tools for visual programming and creating and debugging robot applications. Developers can often interact with robots through webbased or visual interfaces.
One objective of a robotics suite is to support a variety of different robot platforms through a common programming interface. The key point about a robotics suite is that the same code will run either with a simulated robot or the corresponding real robot without modification.

Autonomy levels

Control systems may also have varying levels of autonomy.
Direct interaction is used for haptic or tele-operated devices, and the human has nearly complete control over the robot's motion.
Operator-assist modes have the operator commanding medium-to-high-level tasks, with the robot automatically figuring out how to achieve them.
An autonomous robot may go for extended periods of time without human interaction. Higher levels of autonomy do not necessarily require more complex cognitive capabilities. For example, robots in assembly plants are completely autonomous, but operate in a fixed pattern.
An other classification takes in account the interaction between human control and the machine motions.
Teleoperation. A human controls each movement, each machine actuator change is specified by the operator.
Supervisory. A human specifies general moves or position changes and the machine decides specific movements of its actuators.
Task-level autonomy. The operator specifies only the task and the robot manages itself to complete it.
Fully autonomy. The machine will create and complete all its tasks without human interaction

The mechanical structure

The mechanical structure of a robot must be controlled to perform tasks. The control of a robot involves three distinct phases - perception, processing, and action (robotic paradigms). Sensors give information about the environment or the robot itself (e.g. the position of its joints or its end effector). This information is then processed to calculate the appropriate signals to the actuators (motors) which move the mechanical.
The processing phase can range in complexity. At a reactive level, it may translate raw sensor information directly into actuator commands. Sensor fusion may first be used to estimate parameters of interest (e.g. the position of the robot's gripper) from noisy sensor data. An immediate task (such as moving the gripper in a certain direction) is inferred from these estimates. Techniques from control theory convert the task into commands that drive the actuators.