An intelligible implementation of FastSLAM2.0 on a low-power embedded architecture

Jim�nez Serrata, Albert A.; Yang, Shufan; Li, Renfa

Abstract

The simultaneous localisation and mapping (SLAM) algorithm has drawn increasing interests in autonomous robotic systems. However, SLAM has not been widely explored in embedded system design spaces yet due to the limitation of processing recourses in embedded systems. Especially when landmarks are not identifiable, the amount of computer processing will dramatically increase due to unknown data association. In this work, we propose an intelligible SLAM solution for an embedded processing platform to reduce computer processing time using a low-variance resampling technique. Our prototype includes a low-cost pixy camera, a Robot kit with L298N motor board and Raspberry Pi V2.0. Our prototype is able to recognise artificial landmarks in a real environment with an average 75% of identified landmarks in corner detection and corridor detection with only average 1.14 W.

• Journal Article Type: Article
• Acceptance Date: Feb 9, 2017
• Online Publication Date: Mar 2, 2017
• Publication Date: 2017
• Deposit Date: Mar 11, 2021
• Publicly Available Date: Mar 15, 2021
• Journal: EURASIP Journal on Embedded Systems
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 2017
• Issue: 1
• Article Number: 27 (2017)
• DOI: https://doi.org/10.1186/s13639-017-0075-9
• Keywords: Simultaneous localisation and mapping, Robotics, Embedded systems, Pixy camera
• Public URL: http://researchrepository.napier.ac.uk/Output/2752363