Issue No. 02 - Feb. (2013 vol. 35)
Danping Zou , Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
Ping Tan , Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
This paper studies the problem of vision-based simultaneous localization and mapping (SLAM) in dynamic environments with multiple cameras. These cameras move independently and can be mounted on different platforms. All cameras work together to build a global map, including 3D positions of static background points and trajectories of moving foreground points. We introduce intercamera pose estimation and intercamera mapping to deal with dynamic objects in the localization and mapping process. To further enhance the system robustness, we maintain the position uncertainty of each map point. To facilitate intercamera operations, we cluster cameras into groups according to their view overlap, and manage the split and merge of camera groups in real time. Experimental results demonstrate that our system can work robustly in highly dynamic environments and produce more accurate results in static environments.
Cameras, Simultaneous localization and mapping, Three dimensional displays, Uncertainty, Estimation, Robot vision systems, Robustness
Danping Zou and Ping Tan, "CoSLAM: Collaborative Visual SLAM in Dynamic Environments," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 35, no. 2, pp. 354-366, 2013.