NDLI: A new method for mobile robot arm blind grasping using ultrasonic sensors and Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Hui Liu Stoll, N. Junginger, S. Thurow, K.
Copyright Year	2013
Description	Author affiliation: Center for Life Sci. Autom. (celisca), Univ. of Rostock, Rostock, Germany (Hui Liu; Thurow, K.) \|\| Inst. of Autom., Univ. of Rostock, Rostock, Germany (Junginger, S.) \|\| Center for Life Sci. Autom. (celisca), Rostock, Germany (Stoll, N.)
Abstract	The paper presents a new method to realize mobile robot arm grasping in indoor laboratory environments. This method adopts a blind strategy, which does not need the robot arms be mounted any kind sensors and avoid calculating the complex kinematic equations of the arms. The method includes: (a) two robot on-board ultrasonic sensors in base are utilized to measure the distances between the robot base and the front arm grasping tables; (b) an Artificial Neural Networks (ANN) is proposed to learn/establish the nonlinear relationship between the ultrasonic distances and the joint controlling values. After executing the training step using sampling data, the ANN can forecast/generate the next-step joint controlling values fast and accurately by inputting a new pair of real-time ultrasonic measured distances; (c) to let the blind strategy matching with the transportation process, an arm controlling component with user interfaces is developed; and (d) a method named training arm is adopted to prepare the training data for the training procedure of the ANN model. Finally, an experiment proves that the proposed strategy has good performance in both of the accuracy and the real-time computation, which can be applied to the real-time arm operations for the mobile robot transportation in laboratory automation.
Sponsorship	IEEE Robot. Autom. Soc.
Starting Page	1360
Ending Page	1364
File Size	1403134
Page Count	5
File Format	PDF
ISBN	9781479927449
DOI	10.1109/ROBIO.2013.6739654
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Artificial neural networks Mobile robots Joints Training Transportation Robot sensing systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A neural network approach to robot localization using ultrasonic sensors

Arm grasping for mobile robot transportation using Kinect sensor and kinematic analysis

Ultrasonic sensing based robot localization using entropy nets

Feature localization using neural networks for cleaning robots with ultrasonic sensors

A method proposed for training an artificial neural network used for industrial robot programming by demonstration

Mobile robot navigation using neural Q-learning

Using a Mobile Robot as an Educational Tool

Ultrasonic sensor data fusion for environment recognition

Artificial neural networks for mobile robot acquiring heading angle

A new method for mobile robot arm blind grasping using ultrasonic sensors and Artificial Neural Networks

Similar Documents

A neural network approach to robot localization using ultrasonic sensors

Arm grasping for mobile robot transportation using Kinect sensor and kinematic analysis

Ultrasonic sensing based robot localization using entropy nets

Feature localization using neural networks for cleaning robots with ultrasonic sensors

A method proposed for training an artificial neural network used for industrial robot programming by demonstration

Mobile robot navigation using neural Q-learning

Using a Mobile Robot as an Educational Tool

Ultrasonic sensor data fusion for environment recognition

Artificial neural networks for mobile robot acquiring heading angle

A new method for mobile robot arm blind grasping using ultrasonic sensors and Artificial Neural Networks