6
Biologically Inspired Robotics
FIGURE 1.5
Design of a robotic snake by Z. Liu et al. (2006).
on the basis of sensory motor control. Biological systems are controlled by
expansion and contraction of the muscles based on information collected by
the biological sensors such as eyes, skin, ears, nose, etc. Robotic systems are
controlled based on information feedback from robotic sensors using their
actuators. The underlying principle for both robotic and biological systems
is feedback control. Traditionally, researchers have designed control algorithms for robots using conventional methodologies and theories in controlling engineering. Different from traditional approaches, biologically inspired
controllers are designed based on new philosophy inspired by biological systems. Typical examples of biologically inspired approaches for robot control
are behavior control, proposed by Brooks at the Massachusetts Institute of
Technology (Brooks 1987); iterative learning control, developed by Arimoto
et al. (1985); and intelligent control methods including genetic algorithms
(Parker, Khoogar, and Goldberg 1989) and swarm control (Fukuda and
Kawauchi 1990).
Behavior control was originally developed to solve the problem of motion
control for mobile robots. Traditionally, researchers have followed the procedure of sensing–perception–planning–control for controlling the motion of a
mobile robot. In this method, the robot first uses its sensors to acquire information from the surrounding environment. Second, the acquired information is processed and interpreted. As the third step, a motion is planned for
the robot based on the information interpreted. Finally, the robot executes
the planned motion. It was found that this sequential approach was not very
useful for navigation of mobile robots because it took a lot of time to process and interpret the information and to plan the motion. Behavior control
employs the idea of reactive control, which is a typical behavior of biological
Biologically Inspired Robotics
FIGURE 1.5
Design of a robotic snake by Z. Liu et al. (2006).
on the basis of sensory motor control. Biological systems are controlled by
expansion and contraction of the muscles based on information collected by
the biological sensors such as eyes, skin, ears, nose, etc. Robotic systems are
controlled based on information feedback from robotic sensors using their
actuators. The underlying principle for both robotic and biological systems
is feedback control. Traditionally, researchers have designed control algorithms for robots using conventional methodologies and theories in controlling engineering. Different from traditional approaches, biologically inspired
controllers are designed based on new philosophy inspired by biological systems. Typical examples of biologically inspired approaches for robot control
are behavior control, proposed by Brooks at the Massachusetts Institute of
Technology (Brooks 1987); iterative learning control, developed by Arimoto
et al. (1985); and intelligent control methods including genetic algorithms
(Parker, Khoogar, and Goldberg 1989) and swarm control (Fukuda and
Kawauchi 1990).
Behavior control was originally developed to solve the problem of motion
control for mobile robots. Traditionally, researchers have followed the procedure of sensing–perception–planning–control for controlling the motion of a
mobile robot. In this method, the robot first uses its sensors to acquire information from the surrounding environment. Second, the acquired information is processed and interpreted. As the third step, a motion is planned for
the robot based on the information interpreted. Finally, the robot executes
the planned motion. It was found that this sequential approach was not very
useful for navigation of mobile robots because it took a lot of time to process and interpret the information and to plan the motion. Behavior control
employs the idea of reactive control, which is a typical behavior of biological