Silva Bruno, Vieira Diogo, Gomes Manuel, Oliveira Miguel Riem, Pedrosa Eurico
Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal.
Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal.
Sensors (Basel). 2025 Apr 16;25(8):2501. doi: 10.3390/s25082501.
The calibration of mobile manipulators requires accurate estimation of both the transformations provided by the localization system and the transformations between sensors and the motion coordinate system. Current works offer limited flexibility when dealing with mobile robotic systems with many different sensor modalities. In this work, we propose a calibration approach that simultaneously estimates these transformations, enabling precise calibration even when the localization system is imprecise. This approach is integrated into Atomic Transformations Optimization Method (ATOM), a versatile calibration framework designed for multi-sensor, multi-modal robotic systems. By formulating calibration as an extended optimization problem, ATOM estimates both sensor poses and calibration pattern positions. The proposed methodology is validated through simulations and real-world case studies, demonstrating its effectiveness in improving calibration accuracy for mobile manipulators equipped with diverse sensor modalities.
移动操纵器的校准需要精确估计定位系统提供的变换以及传感器与运动坐标系之间的变换。在处理具有多种不同传感器模态的移动机器人系统时，当前的方法灵活性有限。在这项工作中，我们提出了一种校准方法，可同时估计这些变换，即使定位系统不准确也能实现精确校准。这种方法被集成到原子变换优化方法（ATOM）中，ATOM是一个为多传感器、多模态机器人系统设计的通用校准框架。通过将校准表述为一个扩展的优化问题，ATOM可以估计传感器位姿和校准图案位置。所提出的方法通过仿真和实际案例研究得到验证，证明了其在提高配备多种传感器模态的移动操纵器校准精度方面的有效性。
