The paper introduces a radar signal processing method for goal-oriented, collision-free navigation in mobile robotic platforms. The derived algorithm creates an enhanced perception of the area in front of the sensor through accumulating a sequence of radar pulses that is constantly updated, and uses previously obtained perception to inform future robot steering actions on the fly, thus creating a form of working memory. The algorithm is analytically described, and experimentally confirmed in laboratory conditions with a ground mobile robot operating in real-time.
|Title of host publication||2020 IEEE Radar Conference, RadarConf 2020|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Publication status||Published - 21 Sep 2020|
|Event||2020 IEEE Radar Conference, RadarConf 2020 - Florence, Italy|
Duration: 21 Sep 2020 → 25 Sep 2020
|Name||IEEE National Radar Conference - Proceedings|
|Conference||2020 IEEE Radar Conference, RadarConf 2020|
|Period||21/09/20 → 25/09/20|
Bibliographical noteFunding Information:
This work was supported in part by the National Key R&D Program of China (Grant No. 2018YFE0202101, 2018YFE0202102) and the China Scholarship Council. 978-1-7281-8942-0/20/$31.00 ©2020 IEEE
© 2020 IEEE.
Copyright 2020 Elsevier B.V., All rights reserved.
- Cognitive radar
- Collision avoidance
- Map Memory
- Vector Field Histogram
ASJC Scopus subject areas
- Electrical and Electronic Engineering