We propose a new mapping method based on Normal Distribution Transform Occupancy Maps (NDT-OM) for environment exploration. Our goal is to propose a new architecture which can be used by an industrial mobile robot in a priori unknown environment. The mobile robot introduced in a new environment has to explore the workspace, localize itself and build a map. Current state of the art methods require storing all data collected during this stage and finally build a dense model of the environment. We propose a method which allows building local dense maps of the environment which are organized in a graph-like structure. The change in the registered trajectory of the robot, which may occur after loop closure detection, can be easily utilized by our architecture. Finally, we build a global map which can be later used for collision checking and motion planning.

 

References:
[1]  D. Belter, K. Piaskowski, R. Staszak, Keyframe-based Local Normal Distribution Transform Occupancy Maps for Environment Mapping, IEEE International Conference on Emerging Technologies and Factory Automation, pp. 706-712, 2018