Limits...
Evolution of prehension ability in an anthropomorphic neurorobotic arm.

Massera G, Cangelosi A, Nolfi S - Front Neurorobot (2007)

Bottom Line: In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment.The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Science and Technologies, National Research Council (CNR) Italy.

ABSTRACT
In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.

No MeSH data available.


Related in: MedlinePlus

The kinematic chain of the arm and of the hand. Cylinders represent rotational DOFs. The axes of cylinders indicate the corresponding axis of rotation. The links amongst cylinders represents the rigid connections that make up the arm structure.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2533584&req=5

Figure 1: The kinematic chain of the arm and of the hand. Cylinders represent rotational DOFs. The axes of cylinders indicate the corresponding axis of rotation. The links amongst cylinders represents the rigid connections that make up the arm structure.

Mentions: The arm (Figure 1A) consists mainly of three elements (the arm, the forearm and the wrist) connected through articulations displaced into the shoulder, the arm, the elbow, the forearm and wrist. The shoulder is composed of a sphere with a radius 2.8 cm. The length of arm and forearm is 23 and 18 cm, respectively. The wrist consists of an ellipsoide with a radius of 1.45, 1.2 and 1.45 cm along x-, y- and z-axis, respectively. The joints A, B and C (Figure 1A) provide abduction/adduction, extension/flexion and supination/pronation of the arm in the range [−140°, +60°], [−90°, +90°] and [−60°, +90°], respectively. These three DOFs acts like a ball-and-socket joint moving the arm in a way analogous to the human shoulder joint. The fourth DOF (D) located in the elbow is constituted by a hinge joint which provides extension/flexion within the [−170°, +0°] range (radius–ulna bones). The fifth DOF (E) twists forearm providing pronation/supination of the wrist–hand in the range [−90°, +90°]. The sixth and seventh DOFs (F and G) on the wrist provide flexion/extension and abduction/adduction of the hand within [−30°, +30°] and [−90°, +90°] ranges, respectively.


Evolution of prehension ability in an anthropomorphic neurorobotic arm.

Massera G, Cangelosi A, Nolfi S - Front Neurorobot (2007)

The kinematic chain of the arm and of the hand. Cylinders represent rotational DOFs. The axes of cylinders indicate the corresponding axis of rotation. The links amongst cylinders represents the rigid connections that make up the arm structure.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2533584&req=5

Figure 1: The kinematic chain of the arm and of the hand. Cylinders represent rotational DOFs. The axes of cylinders indicate the corresponding axis of rotation. The links amongst cylinders represents the rigid connections that make up the arm structure.
Mentions: The arm (Figure 1A) consists mainly of three elements (the arm, the forearm and the wrist) connected through articulations displaced into the shoulder, the arm, the elbow, the forearm and wrist. The shoulder is composed of a sphere with a radius 2.8 cm. The length of arm and forearm is 23 and 18 cm, respectively. The wrist consists of an ellipsoide with a radius of 1.45, 1.2 and 1.45 cm along x-, y- and z-axis, respectively. The joints A, B and C (Figure 1A) provide abduction/adduction, extension/flexion and supination/pronation of the arm in the range [−140°, +60°], [−90°, +90°] and [−60°, +90°], respectively. These three DOFs acts like a ball-and-socket joint moving the arm in a way analogous to the human shoulder joint. The fourth DOF (D) located in the elbow is constituted by a hinge joint which provides extension/flexion within the [−170°, +0°] range (radius–ulna bones). The fifth DOF (E) twists forearm providing pronation/supination of the wrist–hand in the range [−90°, +90°]. The sixth and seventh DOFs (F and G) on the wrist provide flexion/extension and abduction/adduction of the hand within [−30°, +30°] and [−90°, +90°] ranges, respectively.

Bottom Line: In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment.The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.

View Article: PubMed Central - PubMed

Affiliation: Institute of Cognitive Science and Technologies, National Research Council (CNR) Italy.

ABSTRACT
In this paper, we show how a simulated anthropomorphic robotic arm controlled by an artificial neural network can develop effective reaching and grasping behaviour through a trial and error process in which the free parameters encode the control rules which regulate the fine-grained interaction between the robot and the environment and variations of the free parameters are retained or discarded on the basis of their effects at the level of the global behaviour exhibited by the robot situated in the environment. The obtained results demonstrate how the proposed methodology allows the robot to produce effective behaviours thanks to its ability to exploit the morphological properties of the robot's body (i.e. its anthropomorphic shape, the elastic properties of its muscle-like actuators and the compliance of its actuated joints) and the properties which arise from the physical interaction between the robot and the environment mediated by appropriate control rules.

No MeSH data available.


Related in: MedlinePlus