Learning of biologically inspired behaviors for autonomous robots by a navigational network

2008 ◽  
Author(s):  
Paulo A. Jimenez ◽  
Bijan Shirinzadeh ◽  
Yongmin Zhong
Keyword(s):  
Autonomous Robots ◽  
Biologically Inspired

scholarly journals A Triboelectric-Based Artificial Whisker for Reactive Obstacle Avoidance and Local Mapping

Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Peng Xu ◽  
Xingyu Wang ◽  
Siyuan Wang ◽  
Tianyu Chen ◽  
Jianhua Liu ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Robots ◽  
Tactile Sensor ◽  
Triboelectric Nanogenerator ◽  
Tactile Sensors ◽  
Biologically Inspired ◽  
External Stimulation ◽  
Autonomous Surface Vehicles ◽  
Electrostatic Induction ◽  
Contact Position

Since designing efficient tactile sensors for autonomous robots is still a challenge, this paper proposes a perceptual system based on a bioinspired triboelectric whisker sensor (TWS) that is aimed at reactive obstacle avoidance and local mapping in unknown environments. The proposed TWS is based on a triboelectric nanogenerator (TENG) and mimics the structure of rat whisker follicles. It operates to generate an output voltage via triboelectrification and electrostatic induction between the PTFE pellet and copper films (0.3 mm thickness), where a forced whisker shaft displaces a PTFE pellet (10 mm diameter). With the help of a biologically inspired structural design, the artificial whisker sensor can sense the contact position and approximate the external stimulation area, particularly in a dark environment. To highlight this sensor’s applicability and scalability, we demonstrate different functions, such as controlling LED lights, reactive obstacle avoidance, and local mapping of autonomous surface vehicles. The results show that the proposed TWS can be used as a tactile sensor for reactive obstacle avoidance and local mapping in robotics.

Bio-Inspired Polarization Vision Techniques for Robotics Applications

2015 ◽  
pp. 81-117 ◽  
Author(s):  
Abd El Rahman Shabayek ◽  
Olivier Morel ◽  
David Fofi
Keyword(s):  
Computer Vision ◽  
Autonomous Robots ◽  
Light Polarization ◽  
Polarization Vision ◽  
Animal Kingdom ◽  
Biologically Inspired ◽  
Distinctive Features ◽  
Comprehensive Survey ◽  
Common Problems ◽  
And Robotics

Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based visual behavior in the animal kingdom. Then, they go in depth with bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization-based techniques and how they are biologically inspired.

A GOAL-ORIENTATION FRAMEWORK FOR SELF-ORGANIZING CONTROL

2013 ◽  
Vol 16 (02n03) ◽  
pp. 1350002
Author(s):  
FRANK HESSE ◽  
FLORENTIN WÖRGÖTTER
Keyword(s):  
Goal Orientation ◽  
Adaptive Learning ◽  
Autonomous Robots ◽  
Self Organization ◽  
Biologically Inspired ◽  
Motor Primitives ◽  
Biologically Inspired Robots ◽  
System A ◽  
Open Question ◽  
Adaptive Learning Systems

Self-organization, especially in the framework of embodiment in biologically inspired robots, allows the acquisition of behavioral primitives by autonomous robots themselves. However, it is an open question how self-organization of basic motor primitives and goal-orientation can be combined, which is a prerequisite for the usefulness of such systems. In the paper at hand we propose a goal-orientation framework allowing the combination of self-organization and goal-orientation for the control of autonomous robots in a mutually independent fashion. Self-organization based motor primitives are employed to achieve a given goal. This requires less initial knowledge about the properties of robot and environment and increases adaptivity of the overall system. A combination of self-organization and reward-based learning seems thus a promising route for the development of adaptive learning systems.

Bio-Inspired Polarization Vision Techniques for Robotics Applications

2018 ◽  
pp. 421-457
Author(s):  
Abd El Rahman Shabayek ◽  
Olivier Morel ◽  
David Fofi
Keyword(s):  
Computer Vision ◽  
Autonomous Robots ◽  
Light Polarization ◽  
Polarization Vision ◽  
Animal Kingdom ◽  
Biologically Inspired ◽  
Distinctive Features ◽  
Comprehensive Survey ◽  
Common Problems ◽  
And Robotics

Researchers have been inspired by nature to build the next generation of smart robots. Based on the mechanisms adopted by the animal kingdom, research teams have developed solutions to common problems that autonomous robots faced while performing basic tasks. Polarization-based behaviour is one of the most distinctive features of some species of the animal kingdom. Light polarization parameters significantly expand visual capabilities of autonomous robots. Polarization vision can be used for most tasks of color vision, like object recognition, contrast enhancement, camouflage breaking, and signal detection and discrimination. In this chapter, the authors briefly cover polarization-based visual behavior in the animal kingdom. Then, they go in depth with bio-inspired applications based on polarization in computer vision and robotics. The aim is to have a comprehensive survey highlighting the key principles of polarization-based techniques and how they are biologically inspired.

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