Unmanned Systems

The market for service robots is predicted to grow significantly in the next decade, but improvements in core technologies of service robots are required before they can be reliable enough for commercial use. Among these technologies, low-cost solutions for fast and accurate localization in unstructured environments are of utmost importance mainly because of two reasons. First, localization is a precursor to autonomous operation; and second, localization is often an integral part of the robot tasks in any applications. The ACIS research group focus on the simultaneous localization and mapping (SLAM) of mobile service robots. The group have specified two strategies to tackle SLAM problem. One strategy focuses on the development of a priori information-based SLAM to facilitate large-scale mapping and fast localization of dynamic landmarks, which are of great importance to not only individual service robots but also sensor network of a group of cooperative robots. The second strategy focuses on the application of sensor and data fusion to the state-space (full-form) and canonical (information-form) SLAM to improve the estimation quality and robustness of the map updating process. The two strategies will converge to develop and implement a VSLAM method with unprecedented accuracy, reliability, and computational efficiency. For relevant modules developed at ACIS.

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