Featured Research

from universities, journals, and other organizations

Guessing Robots Predict Their Environments, Navigate Better

Date:
June 13, 2007
Source:
Purdue University
Summary:
Engineers at Purdue University are developing robots able to make "educated guesses" about what lies ahead as they traverse unfamiliar surroundings, reducing the amount of time it takes to successfully navigate those environments. The method works by using a new software algorithm that enables a robot to create partial maps as it travels through an environment for the first time. The robot refers to this partial map to predict what lies ahead.

C.S. George Lee, from left, a Purdue professor of electrical and computer engineering, works with doctoral student H. Jacky Chang to operate mobile robots using a software algorithm that enables robots to make "educated guesses" about what lies ahead as they traverse unfamiliar surroundings. The approach reduces the amount of time it takes to successfully navigate those environments. Future research will extend the concept to four robots working as a team to explore an unknown environment by sharing the mapped information through a wireless network.
Credit: Purdue News Service photo/David Umberger

Engineers at Purdue University are developing robots able to make "educated guesses" about what lies ahead as they traverse unfamiliar surroundings, reducing the amount of time it takes to successfully navigate those environments.

The method works by using a new software algorithm that enables a robot to create partial maps as it travels through an environment for the first time. The robot refers to this partial map to predict what lies ahead.

The more repetitive the environment, the more accurate the prediction and the easier it is for the robot to successfully navigate, said C.S. George Lee, a Purdue professor of electrical and computer engineering who specializes in robotics.

"For example, it's going to be easier to navigate a parking garage using this map because every floor is the same or very similar, and the same could be said for some office buildings," he said.

Both simulated and actual robots in the research used information from a laser rangefinder and odometer to measure the environment and create the maps of the layout.

The algorithm modifies an approach, called SLAM, which was originated in the 1980s. The name SLAM, for simultaneous localization and mapping, was coined in the early 1990s by Hugh F. Durrant-Whyte and John J. Leonard, then engineers at the University of Oxford in the United Kingdom.

SLAM uses data from sensors to orient a robot by drawing maps of the immediate environment. Because the new method uses those maps to predict what lies ahead, it is called P-SLAM.

"Its effectiveness depends on the presence of repeated features, similar shapes and symmetric structures, such as straight walls, right-angle corners and a layout that contains similar rooms," Lee said. "This technique enables a robot to make educated guesses about what lies ahead based on the portion of the environment already mapped."

Research findings were detailed in a paper that appeared in April in IEEE Transactions on Robotics, published by the Institute of Electrical and Electronics Engineers. The paper was authored by doctoral student H. Jacky Chang, Lee, assistant professor Yung-Hsiang Lu and associate professor Y. Charlie Hu, all in Purdue's School of Electrical and Computer Engineering.

Potential applications include domestic robots and military and law enforcement robots that search buildings and other environments.

The Purdue researchers tested their algorithm in both simulated robots and in a real robot navigating the corridors of a building on the Purdue campus. Findings showed that a simulated robot using the algorithms was able to successfully navigate a virtual maze while exploring 33 percent less of the environment than would ordinarily be required.

Future research will extend the concept to four robots working as a team, operating with ant-like efficiency to explore an unknown environment by sharing the mapped information through a wireless network. The researchers also will work toward creating an "object-based prediction" that recognizes elements such as doors and chairs, as well as increasing the robots' energy efficiency.

Robots operating without the knowledge contained in the maps must rely entirely on sensors to guide them through the environment. Those sensors, however, are sometimes inaccurate, and mechanical errors also cause the robot to stray slightly off course.

The algorithm enables robots to correct such errors by referring to the map, navigating more precisely and efficiently.

"When the robot makes a turn to round a corner, let's say there is some mechanical error and it turns slightly too sharp or not sharply enough," Lee said. "Then, if the robot continues to travel in a straight line that small turning error will result in a huge navigation error in the long run."

The research has been funded by the National Science Foundation.

In separate work, Purdue undergraduate students in a senior design class have developed a prototype firefighting robot called Firebot.


Story Source:

The above story is based on materials provided by Purdue University. Note: Materials may be edited for content and length.


Cite This Page:

Purdue University. "Guessing Robots Predict Their Environments, Navigate Better." ScienceDaily. ScienceDaily, 13 June 2007. <www.sciencedaily.com/releases/2007/06/070612152446.htm>.
Purdue University. (2007, June 13). Guessing Robots Predict Their Environments, Navigate Better. ScienceDaily. Retrieved September 2, 2014 from www.sciencedaily.com/releases/2007/06/070612152446.htm
Purdue University. "Guessing Robots Predict Their Environments, Navigate Better." ScienceDaily. www.sciencedaily.com/releases/2007/06/070612152446.htm (accessed September 2, 2014).

Share This




More Computers & Math News

Tuesday, September 2, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Google's Self-Driving Car Still Has Many Flaws

Google's Self-Driving Car Still Has Many Flaws

Newsy (Sep. 1, 2014) You've seen a lot of Google's self-driving car, but that doesn't mean it's coming soon. A new report says the vehicle is nowhere near road ready. Video provided by Newsy
Powered by NewsLook.com
Apple's Rumored iWatch Could Cost $400

Apple's Rumored iWatch Could Cost $400

Newsy (Aug. 31, 2014) Apple is expected to charge a premium for its still-rumored wearable device. Video provided by Newsy
Powered by NewsLook.com
Amazon Chases Netflix And HBO With Five New Pilots

Amazon Chases Netflix And HBO With Five New Pilots

Newsy (Aug. 31, 2014) Amazon has released another batch of five pilots, allowing viewers to vote on which shows will get full seasons on the company's streaming service. Video provided by Newsy
Powered by NewsLook.com
Apple Wants Your iPhone To Become Your Wallet

Apple Wants Your iPhone To Become Your Wallet

Newsy (Aug. 31, 2014) Apple might soon announce a feature that would allow iPhones to act as a credit card when making payments in physical stores. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:
from the past week

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins