NDLI: An unsupervised adaptive strategy for constructing probabilistic roadmaps

Content Provider	IEEE Xplore Digital Library
Author	Tapia, L. Thomas, S. Boyd, B. Amato, N.M.
Copyright Year	2009
Description	Author affiliation: Parasol Lab., Dept. of Computer Science and Engineering, Texas A&M Univ., College Station, 77843-3112, USA (Tapia, L.; Thomas, S.; Boyd, B.; Amato, N.M.)
Abstract	Since planning environments are complex and no single planner exists that is best for all problems, much work has been done to explore methods for selecting where and when to apply particular planners. However, these two questions have been difficult to answer, even when adaptive methods meant to facilitate a solution are applied. For example, adaptive solutions such as setting learning rates, hand-classifying spaces, and defining parameters for a library of planners have all been proposed. We demonstrate a strategy based on unsupervised learning methods that makes adaptive planning more practical. The unsupervised strategies require less user intervention, model the topology of the problem in a reasonable and efficient manner, can adapt the sampler depending on characteristics of the problem, and can easily accept new samplers as they become available. Through a series of experiments, we demonstrate that in a wide variety of environments, the regions automatically identified by our technique represent the planning space well both in number and placement.We also show that our technique has little overhead and that it out-performs two existing adaptive methods in all complex cases studied.
Starting Page	4037
Ending Page	4044
File Size	535104
Page Count	8
File Format	PDF
ISBN	9781424427888
ISSN	10504729
DOI	10.1109/ROBOT.2009.5152544
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-12
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Strategic planning Libraries Unsupervised learning Machine learning Design automation Robotics and automation Computer science USA Councils Topology
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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

Adaptive workspace biasing for sampling-based planners

An adaptive roadmap guided Multi-RRTs strategy for single query path planning

Analysis of probabilistic roadmaps for path planning

A skill-based motion planning framework for humanoids

Generalized direction changing fall control of humanoid robots among multiple objects

Evader surveillance under incomplete information

A dynamic subgoal path planner for unpredictable environments

Prediction-based reactive control strategy for human-robot interactions

Towards One Shot Learning by imitation for humanoid robots

An unsupervised adaptive strategy for constructing probabilistic roadmaps

Similar Documents

Adaptive workspace biasing for sampling-based planners

An adaptive roadmap guided Multi-RRTs strategy for single query path planning

Analysis of probabilistic roadmaps for path planning

A skill-based motion planning framework for humanoids

Generalized direction changing fall control of humanoid robots among multiple objects

Evader surveillance under incomplete information

A dynamic subgoal path planner for unpredictable environments

Prediction-based reactive control strategy for human-robot interactions

Towards One Shot Learning by imitation for humanoid robots

An unsupervised adaptive strategy for constructing probabilistic roadmaps