Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Robotic autonomous behavior selection using episodic memory and attention system

Robotic autonomous behavior selection using episodic memory and attention system PurposeThis paper aims to focus on the autonomous behavior selection issue of robotics from the perspective of episodic memory in cognitive neuroscience with biology-inspired attention system. It instructs a robot to follow a sequence of behaviors. This is similar to human travel to a target location by guidance.Design/methodology/approachThe episodic memory-driving Markov decision process is proposed to simulate the organization of episodic memory by introducing neuron stimulation mechanism. Based on the learned episodic memory, the robotic global planning method is proposed for efficient behaviors sequence prediction using bottom-up attention. Local behavior planning based on risk function and feasible paths is used for behavior reasoning under imperfect memory. Aiming at the problem of whole target selection under redundant environmental information, a top-down attention servo control method is proposed to effectively detect the target containing multi-parts and distractors which share same features with the target.FindingsBased on the proposed method, the robot is able to accumulate experience through memory, and achieve adaptive behavior planning, prediction and reasoning between tasks, environment and threats. Experimental results show that the method can balance the task objectives, select the suitable behavior according to current environment.Originality/valueThe behavior selection method is integrated with cognitive levels to generate optimal behavioral sequence. The challenges in robotic planning under uncertainty and the issue of target selection under redundant environment are addressed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Industrial Robot: An International Journal Emerald Publishing

Robotic autonomous behavior selection using episodic memory and attention system

Download PDF
10 pages

Loading next page...
 
/lp/emerald-publishing/robotic-autonomous-behavior-selection-using-episodic-memory-and-BeNdU2QPBC

References (22)

Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0143-991X
DOI
10.1108/IR-09-2016-0250
Publisher site
See Article on Publisher Site

Abstract

PurposeThis paper aims to focus on the autonomous behavior selection issue of robotics from the perspective of episodic memory in cognitive neuroscience with biology-inspired attention system. It instructs a robot to follow a sequence of behaviors. This is similar to human travel to a target location by guidance.Design/methodology/approachThe episodic memory-driving Markov decision process is proposed to simulate the organization of episodic memory by introducing neuron stimulation mechanism. Based on the learned episodic memory, the robotic global planning method is proposed for efficient behaviors sequence prediction using bottom-up attention. Local behavior planning based on risk function and feasible paths is used for behavior reasoning under imperfect memory. Aiming at the problem of whole target selection under redundant environmental information, a top-down attention servo control method is proposed to effectively detect the target containing multi-parts and distractors which share same features with the target.FindingsBased on the proposed method, the robot is able to accumulate experience through memory, and achieve adaptive behavior planning, prediction and reasoning between tasks, environment and threats. Experimental results show that the method can balance the task objectives, select the suitable behavior according to current environment.Originality/valueThe behavior selection method is integrated with cognitive levels to generate optimal behavioral sequence. The challenges in robotic planning under uncertainty and the issue of target selection under redundant environment are addressed.

Journal

Industrial Robot: An International Journal – Emerald Publishing

Published: May 15, 2017

There are no references for this article.