A Collaborative Visual SLAM Framework for Service Robots

Autor:	Ouyang, Ming, Shi, Xuesong, Wang, Yujie, Tian, Yuxin, Shen, Yingzhe, Wang, Dawei, Wang, Peng, Cao, Zhiqiang
Rok vydání:	2021
Předmět:	Computer Science - Robotics Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We present a collaborative visual simultaneous localization and mapping (SLAM) framework for service robots. With an edge server maintaining a map database and performing global optimization, each robot can register to an existing map, update the map, or build new maps, all with a unified interface and low computation and memory cost. We design an elegant communication pipeline to enable real-time information sharing between robots. With a novel landmark organization and retrieval method on the server, each robot can acquire landmarks predicted to be in its view, to augment its local map. The framework is general enough to support both RGB-D and monocular cameras, as well as robots with multiple cameras, taking the rigid constraints between cameras into consideration. The proposed framework has been fully implemented and verified with public datasets and live experiments. Comment: IROS 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2102.03228 Zobrazit plný text záznamu View this record from Arxiv