A robotic eye controller based on cooperative neural agents

Chang, Oscar; Campoy, Pascual; Martínez, Carol; Olivares-Méndez, Miguel A.

doi:10.1109/ijcnn.2010.5596985

Cited by 3 publications

(3 citation statements)

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“…Under evolutive pressure, agents develop communication skill and cooperative behaviors that raise the level of competence of vision-guided mobile robots, allowing a convenient autonomous exploration of the environment. In [13], a neural behavior-initiating agent (BIA) was proposed to integrate relevant compressed image information coming from other cooperating and specialized neural agents. Using this arrangement, the problem of tracking and recognizing a moving icon was solved by three simpler and separated tasks.…”

Section: Previous Workmentioning

confidence: 99%

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Autonomous Robots and Behavior Initiators

Chang¹

2018

Human-Robot Interaction - Theory and Application

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We use an autonomous neural controller (ANC) that handles the mechanical behavior of virtual, multi-joint robots, with many moving parts and sensors distributed through the robot's body, satisfying basic Newtonian laws. As in living creatures, activities inside the robot include behavior initiators: self-activating networks that burn energy and function without external stimulus. Autonomy is achieved by mimicking the dynamics of biological brains, in resting situations, a default state network (DSN), specialized set of energy burning neurons, assumes control and keeps the robot in a safe condition, where other behaviors can be brought to use. Our ANC contains several kinds of neural nets trained with gradient descent to perform specialized jobs. The first group generates moving wave activities in the robot muscles, the second yields basic position/presence prediction information about sensors, the third acts as timing masters, empowering sequential tasks. We add a fourth category of self-activating networks that push behavior from the inside. Through evolutive methods, the composed network share clue information along a few connecting weights, producing self-motivated robots, capable of achieving noticeable self-level of competence. We show that this spirited robot interacts with humans and, through appropriate interfaces, learn complex behaviors that satisfy unknown, subjacent human expectative.

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Section: Previous Workmentioning

confidence: 99%

“…The neural networks used in this chapter are sigmoidal neurons trained with backpropagation [17]. Other functioning details are given in [12,13].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Autonomous Robots and Behavior Initiators

Chang¹

2018

Human-Robot Interaction - Theory and Application

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“…The approach sought in the prototype aims to replicate some of these capabilities, in particular, evaluated through optical tracking. In [13] a similar system is developed, where the movement of the prototype feeds back to the control software, this allows to produce of the movement of the robot in real-time concerning the image to be followed [14]. Problems related to image disturbance and high-speed motion are not initially considered in this research, focusing the efforts of this first stage on the functional problem (mechanical structure) [15].…”

Section: Introductionmentioning

confidence: 99%

Design of an optical sensor system for robots inspired by the human eye

G¹,

O²,

S³

2022

Global J. Eng. Technol. Adv.

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The development of autonomous motion capability by robotic systems, particularly in dynamic environments, is strongly related to the sensor systems installed in the robot. An important feature of these sensors should be their ability to detect the world in the same way as humans do. This paper focuses on the design of a prototype of a robotic eye, or optical sensor, which has functional characteristics similar to those of the human eye and complies with two Degrees of Freedom (DOF) in its movement. In addition to this, the entire design process of the parts is documented with computer-aided design (CAD) support, the manipulation software, and the programming structure used to control it. The performance tests performed and the analysis of the results obtained demonstrate the total fulfillment of the proposed objectives, which were even surpassed.

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