Autonomous robots are robots which can perform desired tasks in unstructured environments without continuous human guidance. Many kinds of robots have some degree of autonomy. Different robots can be autonomous in different ways. A high degree of autonomy is particularly desirable in fields such as space exploration, cleaning floors, mowing lawns, and waste water treatment.

Some modern factory robots are "autonomous" within the strict confines of their direct environment. It may not be that every degree of freedom exists in their surrounding environment but the factory robot's workplace is challenging and can often contain chaotic, unpredicted variables. The exact orientation and position of the next object of work and (in the more advanced factories) even the type of object and the required task must be determined. This can vary unpredictably (at least from the robot's point of view).

One important area of robotics research is to enable the robot to cope with its environment whether this be on land, underwater, in the air, underground, or in space.

A fully autonomous robot has the ability to

• Gain information about the environment.
• Work for an extended period without human intervention.
• Move either all or part of itself throughout its operating environment without human assistance.
• Avoid situations that are harmful to people, property, or itself unless those are part of its design specifications.

An autonomous robot may also learn or gain new capabilities like adjusting strategies for accomplishing its task(s) or adapting to changing surroundings.

Autonomous robots still require regular maintenance, as do other machines.

Researchers concerned with creating true artificial life are concerned not only with intelligent control, but further with the capacity of the robot to find its own resources through foraging (looking for food, which includes both energy and spare parts).

This is related to autonomous foraging, a concern within the sciences of behavioral ecology, social anthropology, and human behavioral ecology; as well as robotics, artificial intelligence, and artificial life.

A hybrid system is a dynamic system that exhibits both continuous and discrete dynamic behavior — a system that can both flow (described by a differential equation) and jump (described by a difference equation). Often, the term "hybrid dynamic system" is used, to distinguish over hybrid systems such as those that combine neural nets and fuzzy logic, or electrical and mechanical drivelines. A hybrid system has the benefit of encompassing a larger class of systems within its structure, allowing for more flexibility in modeling dynamic phenomena.

In general, a hybrid system can be described by a few pieces of information. The state of the system consists of vector signals, which can change according to dynamic laws in the system data. The data includes a flow equation, f(x), which describes the continuous dynamics, a flow set, C, in which flow is permitted, a jump equation, g(x), which describes the discrete dynamics, and a jump set, D, in which discrete state evolution is permitted.

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