Search: onr:"swepub:oai:DiVA.org:umu-50973" >
Robot learning from...
Robot learning from demonstration using predictive sequence learning
-
- Billing, Erik, 1981- (author)
- Umeå universitet,Institutionen för datavetenskap
-
- Hellström, Thomas, 1956- (author)
- Umeå universitet,Institutionen för datavetenskap
-
- Janlert, Lars Erik, 1950- (author)
- Umeå universitet,Institutionen för datavetenskap
-
(creator_code:org_t)
- Kanpur, India : IN-TECH, 2011
- 2011
- English.
-
In: Robotic systems. - Kanpur, India : IN-TECH. - 9789533079417 ; , s. 235-250
- Related links:
-
http://www.intechope...
-
show more...
-
https://mts.intechop...
-
https://urn.kb.se/re...
-
show less...
Abstract
Subject headings
Close
- In this chapter, the prediction algorithm Predictive Sequence Learning (PSL) is presented and evaluated in a robot Learning from Demonstration (LFD) setting. PSL generates hypotheses from a sequence of sensory-motor events. Generated hypotheses can be used as a semi-reactive controller for robots. PSL has previously been used as a method for LFD, but suffered from combinatorial explosion when applied to data with many dimensions, such as high dimensional sensor and motor data. A new version of PSL, referred to as Fuzzy Predictive Sequence Learning (FPSL), is presented and evaluated in this chapter. FPSL is implemented as a Fuzzy Logic rule base and works on a continuous state space, in contrast to the discrete state space used in the original design of PSL. The evaluation of FPSL shows a significant performance improvement in comparison to the discrete version of the algorithm. Applied to an LFD task in a simulated apartment environment, the robot is able to learn to navigate to a specific location, starting from an unknown position in the apartment.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
Keyword
- computer and systems sciences
- data- och systemvetenskap
Publication and Content Type
- ref (subject category)
- kap (subject category)
Find in a library
To the university's database