scholarly journals Visual Perception and the Emergence of Minimal Representation

2021 ◽  
Vol 12 ◽  
Author(s):  
Argyris Arnellos ◽  
Alvaro Moreno
Keyword(s):  
Visual Perception ◽  
Obstacle Avoidance ◽  
Spatial Vision ◽  
Visually Guided ◽  
Minimal Representation ◽  
Structural Representation ◽  
Low Resolution ◽  
Behavioral Studies ◽  
Minimal Form ◽  
Behavior Based

There is a long-lasting quest of demarcating a minimally representational behavior. Based on neurophysiologically-informed behavioral studies, we argue in detail that one of the simplest cases of organismic behavior based on low-resolution spatial vision–the visually-guided obstacle avoidance in the cubozoan medusa Tripedalia cystophora–implies already a minimal form of representation. We further argue that the characteristics and properties of this form of constancy-employing structural representation distinguish it substantially from putative representational states associated with mere sensory indicators, and we reply to some possible objections from the liberal representationalists camp by defending and qualitatively demarcating the minimal nature of our case. Finally, we briefly discuss the implications of our thesis within a naturalistic framework.

Space robot motion path planning based on fuzzy control algorithm

2021 ◽  
pp. 1-8
Author(s):  
Baoyu Shi ◽  
Hongtao Wu
Keyword(s):  
Path Planning ◽  
Fuzzy Control ◽  
Obstacle Avoidance ◽  
Control Algorithm ◽  
Space Robot ◽  
Robot Motion ◽  
Robot Path Planning ◽  
Behavior Based ◽  
Fuzzy Control Algorithm ◽  
Robot Path

Path planning technology is one of the core technologies of intelligent space robot. Combining image recognition technology and artificial intelligence learning algorithm for robot path planning in unknown space environment has become one of the hot research issues. The purpose of this paper is to propose a spatial robot path planning method based on improved fuzzy control, aiming at the shortcomings of path planning in the current industrial space robot motion control process, and based on fuzzy control algorithm. This paper proposes a fuzzy obstacle avoidance method with speed feedback based on the original advantages of the fuzzy algorithm, which improves the obstacle avoidance performance of space robot under continuous obstacles. At the same time, we integrated the improved fuzzy obstacle avoidance strategy into the behavior-based control technology, making the avoidance become an independent behavioral unit. Divide the path planning into a series of relatively independent behaviors such as fuzzy obstacle avoidance, cruise, trend target, and deadlock by the behavior-based method. According to the interaction information between the space robot and the environment, each behavior acquires the dominance of the robot through the competition mechanism, making the robot complete the specific behavior at a certain moment, and finally realize the path planning. Furthermore, to improve the overall fault tolerance of the space, robot we introduced an elegant downgrade strategy, so that the robot can successfully complete the established task in the case of control command deterioration or failure of important information, avoiding the overall performance deterioration effectively. Therefore, through the simulation experiment of the virtual environment platform, MobotSim concluded that the improved algorithm has high efficiency, high security, and the planned path is more in line with the actual situation, and the method proposed in this paper can make the space robot successfully reach the target position and optimize the spatial path, it also has good robustness and effectiveness.

Visually guided obstacle avoidance in box jellyfish

2007 ◽  
Vol 146 (4) ◽  
pp. S181
Author(s):  
A. Garm ◽  
M. O'Connor ◽  
L. Parkefelt ◽  
D. Nilsson
Keyword(s):  
Obstacle Avoidance ◽  
Visually Guided ◽  
Box Jellyfish

Wall Following and Obstacle Avoidance Control in Roisc-v1.0 (Robotic Disinfectant) using Behavior Based Control

2021 ◽  
Author(s):  
Yudha Sadewa ◽  
Eko Henfri Binugroho ◽  
Nofria Hanafi ◽  
Ir. Dadet Pramadihanto ◽  
Achmad Fauzi ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Behavior Based Control ◽  
Avoidance Control ◽  
Behavior Based ◽  
Wall Following

A Task of Miniature Mobile Robot Learning for Obstacle Avoidance through Neural Networks

2012 ◽  
Vol 151 ◽  
pp. 498-502
Author(s):  
Jin Xue Zhang ◽  
Hai Zhu Pan
Keyword(s):  
Neural Networks ◽  
Reinforcement Learning ◽  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Robot Learning ◽  
Q Learning ◽  
Robot Systems ◽  
The Neural Networks ◽  
Behavior Based

This paper is concerned with Q-learning , a very popular algorithm for reinforcement learning ,for obstacle avoidance through neural networks. The principle tells that the focus always must be on both ecological nice tasks and behaviours when designing on robot. Many robot systems have used behavior-based systems since the 1980’s.In this paper, the Khepera robot is trained through the proposed algorithm of Q-learning using the neural networks for the task of obstacle avoidance. In experiments with real and simulated robots, the neural networks approach can be used to make it possible for Q-learning to handle changes in the environment.

Fuzzy Behavior-Based Control for a Task of Three-Link Manipulator with Obstacle Avoidance

1999 ◽  
Vol 11 (6) ◽  
pp. 502-509 ◽  
Author(s):  
Palitha Dassanayake ◽  
◽  
Keigo Watanabe ◽  
Kiyotaka Izumi ◽  
◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Mobile Robots ◽  
Obstacle Avoidance ◽  
Basic Concept ◽  
Online Information ◽  
Acceptable Solution ◽  
Control Approach ◽  
Task Control ◽  
Behavior Based Control ◽  
Behavior Based

Our objective is for a 3-link manipulator to reach a target while avoiding obstacles with online information using a fuzzy-behavior-based control approach. Control applied to mobile robots elsewhere is modified to suit to the manipulator. Fuzzy behavior elements are trained using a genetic algorithm. A component apart from the basic concept is introduced to overcome gravitation. Result shows the manipulator reaches the target with an acceptable solution for 3 simulations, so the proposed approach is suitable to multilink manipulator task control.

Prism adaptation and generalization during visually guided locomotor tasks

2011 ◽  
Vol 106 (2) ◽  
pp. 860-871 ◽  
Author(s):  
M. Scott Alexander ◽  
Brent W. G. Flodin ◽  
Daniel S. Marigold
Keyword(s):  
Nervous System ◽  
Obstacle Avoidance ◽  
Avoidance Task ◽  
Visually Guided ◽  
Initial Exposure ◽  
Foot Placement ◽  
Before And After ◽  
The Right ◽  
Placement Distance ◽  
Precision Stepping

The ability of individuals to adapt locomotion to constraints associated with the complex environments normally encountered in everyday life is paramount for survival. Here, we tested the ability of 24 healthy young adults to adapt to a rightward prism shift (∼11.3°) while either walking and stepping to targets (i.e., precision stepping task) or stepping over an obstacle (i.e., obstacle avoidance task). We subsequently tested for generalization to the other locomotor task. In the precision stepping task, we determined the lateral end-point error of foot placement from the targets. In the obstacle avoidance task, we determined toe clearance and lateral foot placement distance from the obstacle before and after stepping over the obstacle. We found large, rightward deviations in foot placement on initial exposure to prisms in both tasks. The majority of measures demonstrated adaptation over repeated trials, and adaptation rates were dependent mainly on the task. On removal of the prisms, we observed negative aftereffects for measures of both tasks. Additionally, we found a unilateral symmetric generalization pattern in that the left, but not the right, lower limb indicated generalization across the 2 locomotor tasks. These results indicate that the nervous system is capable of rapidly adapting to a visuomotor mismatch during visually demanding locomotor tasks and that the prism-induced adaptation can, at least partially, generalize across these tasks. The results also support the notion that the nervous system utilizes an internal model for the control of visually guided locomotion.

The Effect of Pictorial Illusion on Prehension and Perception

1998 ◽  
Vol 10 (1) ◽  
pp. 122-136 ◽  
Author(s):  
Angela M. Haffenden ◽  
Melvyn A. Goodale
Keyword(s):  
Visual Perception ◽  
Three Dimensional ◽  
Object Size ◽  
Strongly Correlated ◽  
Visually Guided ◽  
Grip Aperture ◽  
Physical Size ◽  
Disk Size ◽  
Dimensional Version ◽  
Size Contrast

The present study examined the effect of a size-contrast illusion (Ebbinghaus or Titchener Circles Illusion) on visual perception and the visual control of grasping movements. Seventeen right-handed participants picked up and, on other trials, estimated the size of fipoker-chipfl disks, which functioned as the target circles in a three-dimensional version of the illusion. In the estimation condition, subjects indicated how big they thought the target was by separating their thumb and forefinger to match the target's size. After initial viewing, no visual feedback from the hand or the target was available. Scaling of grip aperture was found to be strongly correlated with the physical size of the disks, while manual estimations of disk size were biased in the direction of the illusion. Evidently, grip aperture is calibrated to the true size of an object, even when perception of object size is distorted by a pictorial illusion, a result that is consistent with recent suggestions that visually guided prehension and visual perception are mediated by separate visual pathways.

scholarly journals What is the "spectral diet" of humans?

2019 ◽  
Author(s):  
Forrest Webler ◽  
Manuel Spitschan ◽  
Russell Foster ◽  
Marilyne Andersen ◽  
Stuart Peirson
Keyword(s):  
Spatial Distribution ◽  
Visual Perception ◽  
Light Exposure ◽  
Spectral Composition ◽  
Spatial Vision ◽  
Natural Image ◽  
Natural Light ◽  
Natural Image Statistics ◽  
The World ◽  
Long Time

Our visual perception of the world – seeing form and colour or navigating the environment – depends on the interaction of light and matter in the environment. Light also has a more fundamental role in regulating rhythms in physiology and behaviour, as well as in the acute secretion of hormones like melatonin and changes in alertness, where light exposure at short, medium and long-time scales has different effects on these visual and non-visual functions. Yet patterns of light exposure in the real world are inherently messy: we move in and out of buildings and are therefore exposed to mixtures of artificial and natural light, and the physical makeup of our environment can also drastically alter the spectral composition and spatial distribution of the illuminant light. In spatial vision, the examination of natural image statistics has proven to be an important driver in research. Here, we expand this concept to the spectral domain and develop the concept of the “spectral diet” of humans.

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