A Multi-Sensor Next-Best-View Framework for Geometric Model-Based Robotics Applications

Abstract: 

Geometric models are crucial for many robotics applications. Current robotic 3D reconstruction systems only focus on specific reconstruction goals which make them hard to adapt to different tasks. In this paper we present a next-best-view framework which allows robots to construct a geometric model incrementally through consecutive sensing actions. Instead of limiting the type and total number of sensors, in each sensing step we evaluate actions from all available sensors and pick the best to execute. Our framework is more comprehensive since the model building process can be designed to best accomplish different tasks. The system has been demonstrated in two experiments on 3D reconstruction and weld seam inspection, yielding promising results.

Reference:
J. Cui, J.T. Wen, J. Trinkle (2019). A Multi-Sensor Next-Best-View Framework for Geometric Model-Based Robotics Applications.

IEEE International Conference on Robotics and Automation, Montreal, Quebec, Canada, May 2019.

Publication Type: 
Conference Articles