Journal
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Volume 66, Issue 1, Pages 2-13Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2016.2618978
Keywords
Indoor mobile robot; multiple measurements; room-level localization; sonar measurements; structured sparse coding
Funding
- National Key Project for Basic Research, China [2013CB329403]
- National Natural Science Foundation of China [61673238, 91420302, 61327809]
- National High-Tech Research and Development Plan [2015AA042306]
- National Key Research and Development Program [2016YFB0100903]
Ask authors/readers for more resources
In this paper, we aim to achieve robust and cost-effective room-level localization for the indoor mobile robot. It is unrealistic to obtain precise localization information from the sonar sensors because of the sparseness and uncertainty. Our attempts show that the room-level localization can be achieved using sonar sensors by accumulating the sonar data to overcome the limitations of sensor performance. To this end, we formulate the room-level localization as a joint sparse coding problem, which encourages the coding vectors to share the common room sparsity, but different locations. We systematically evaluate the performance of the different coding strategies on the collected sonar measurement data set.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available