At least six fields of research today advanced robotics structure: one that relates the robot with its environment, the behavioral, cognitive, or developmental epigenetics, the evolutionary and biorrobótica. It’s a big field of interdisciplinary study that relies on the mechanical, electrical, electronics and informatics, as well as physical science, anatomy, psychology, biology, zoology and ethology, among others. The basis of this research is embodied Cognitive Science and the New AI. Its purpose: lighting intelligent and autonomous robots that reason, behave, evolve and act like people. By Sergio Moriello.multidisciplinary study, which relies largely on the engineering (mechanical, electrical, electronics and computers) and science (physics, anatomy, psychology, biology, zoology, ethology, etc.).. Refers to highly complex automated systems that have an articulated mechanical structure, governed by an electronic control system, and characteristics of autonomy, reliability, versatility and mobility.
In essence, the “autonomous intelligent robots” are dynamic systems consisting of an electronic controller coupled to a mechanical body. Thus, these machines require adequate sensory systems (to perceive the environment in which they operate), a precise mechanical structure adaptable (to have a certain physical skills of locomotion and manipulation) of complex effector systems (for running the assignments) and sophisticated control systems (to carry out corrective actions when necessary) [Moriello, 2005, p. 172].
Situated Robotics (Situated Robotics)
This approach deals with robots that are embedded in complex and often dynamically changing [Mataric, 2002]. It is based on two central ideas [Florian, 2003] [Muñoz Moreno, 2000] [Innocenti Badano, 2000]: robots) “are embodied” (embodiment), ie, have a suitable physical body to experience its environment so direct where their actions have immediate feedback on their own perceptions, and b) are situated “(situatedness), ie, they are embedded within an environment, interact with the world, which directly influences-its-on behavior.
Obviously, the complexity of the environment has a close relationship with the complexity of the control system. Indeed, if the robot has to react quickly and intelligently in a dynamic and challenging environment, the problem of control becomes very difficult. If the robot, however, need not answer quickly, reducing the complexity required to develop control.
Within this paradigm, there are several subparadigmas: the “Behavior-based robotics,” the “cognitive robotics”, the “epigenetic robotics”, the “evolutionary robotics” and “biomimetic robotics.
Behavior-Based Robotics and Behavior (Behavior-Base Robotics)
This approach uses behavioral principles: robots generate a behavior only when stimulated, ie respond to changes in their local environment (as when someone accidentally touches a hot object). Here, the designer divides tasks into many different basic behaviors, each of which runs on a separate layer of the control system of the robot.
Typically, these modules (behaviors) may be to avoid obstacles, walking, lifting, etc.. The intelligent features of the system, such as perception, planning, modeling, learning, etc.. emerge from interaction between the various modules and the physical environment where the robot is immersed. The system-control-Fully distributed incrementally builds, layer by layer, through a process of trial and error, and each layer is only responsible for basic behavior [Moriello, 2005, p. 177 / 8].
The behavior-based systems are capable of reacting in real time, as calculated directly from the actions of perceptions (through a set of correspondence rules “situation-action). It is important to note that the number of layers increases the complexity of the problem. Thus, a very complex task may be beyond the ability of the designer (it was hard to define all the layers, their interrelationships and dependencies) [Pratiharas, 2003].
Another drawback is that due to the presence of several individual behavior and dynamics of interaction with the world, it is often difficult to say that a series of actions in particular has been the product of a particular behavior. Sometimes several behaviors simultaneously working or are exchanging rapidly.
Although intelligence may reach the insect, probably built systems from this approach have limited skills, as they have internal representations [Dawson, 2002]. Indeed, this type of robots present a great difficulty to execute complex tasks and in the simplest, no guarantee the best solution as optimal.
Cognitive Robotics (Cognitive Robotics)
This approach uses techniques from the field of Cognitive Science. It deals with deploying robots that perceive, reason and act in dynamic environments, unknown and unpredictable. Such robots must have cognitive functions that involve high-level reasoning, for example, about goals, actions, time, cognitive states of other robots, when and what to perceive, learn from experience, and so on.
For that, they must possess an internal symbolic model and their local environment, and sufficient capacity for logical reasoning to make decisions and to perform the tasks necessary to achieve its objectives. In short, this line of work is responsible for implementing cognitive characteristics in robots, such as perception, concept formation, attention, learning, memory, short and long term, etc.. [Bogner, Maletic, Franklin, 2000].
If we achieve that the robots themselves develop their cognitive abilities, is avoid the “hand” for every conceivable contingency task or [Kovacs, 2004]. Also, if the robots is achieved using representations and reasoning mechanisms similar to that of humans, could improve human-computer interaction and collaborative work. However, it needs a high processing power (especially if the robot has many sensors and actuators) and lots of memory (to represent the state space).
Epigenetic Robotics and Development
This approach is characterized in that tries to implement control systems of general purpose through a long process of development or self-autonomous organization. As a result of interaction with their environment, the robot is able to develop different-and increasingly complex-perceptual skills, cognitive and behavioral.
This is a research area that integrates developmental neuroscience, developmental psychology and robotics located. Initially the system can be equipped with a small set of behaviors or innate knowledge, but, thanks to the experience-is able to create more complex representations and actions. In short, this is the machine to independently develop the skills appropriate for a given particular environment transiting through the different stages of their “autonomous mental development.
The difference between robotics and robotics development epigenetic-sometimes grouped under the term “ontogenetic robotics (ontogenetic robotics) – is a subtle thing, as regards the type of environment. Indeed, while the former refers only to the physical environment, the second takes into account the social environment.
The term epigenetic (beyond the genetic) was introduced in psychology, “by Swiss psychologist Jean Piaget to describe his new field of study that emphasizes the individual sensorimotor interaction with the physical environment, rather than take into account only to genes. Moreover, the Russian psychologist Lev Vygotsky supplemented this idea with the importance of social interaction.