Abstract

Abstract
This work presents a six degrees of freedom probabilistic scan matching method for registration of 3D underwater sonar scans. Unlike previous works, where local submaps are built to overcome measurement sparsity, our solution develops scan matching directly from the raw sonar data. Our method, based on the probabilistic Iterative Correspondence (pIC), takes measurement uncertainty into consideration while developing the registration procedure. A new probabilistic sensor model was developed to compute the uncertainty of each scan measurement individually. Initial displacement guesses are obtained from a probabilistic dead reckoning approach, also detailed in this document. Experiments, based on real data, demonstrate superior robustness and accuracy of our method with respect to the popular ICP algorithm. An improved trajectory is obtained by integration of scan matching updates in the localization data fusion algorithm, resulting in a substantial reduction of the original dead reckoning drift.

Abstract

Abstract

Abstract
Underwater autonomous manipulation is the capability of a mobile robot to perform intervention tasks that require physical contact with unstructured environments without continuous human supervision. Being difficult to assess the behaviour of existing motion planner algorithms, this research proposes a new planner evaluation metric to identify well-behaved planners for specialized tasks of inspection and monitoring of man-made underwater structures. This metric is named NEMU and combines three different performance indicators: effectiveness, safety and adaptability. NEMU deals with the randomization of sampling-based motion planners. Moreover, this article presents a benchmark of multiple planners applied to a 6 DoF manipulator operating underwater. Results conducted in real scenarios show that different planners are better suited for different tasks. Experiments demonstrate that the NEMU metric can be used to distinguish the performance of planners for particular movement conditions. Moreover, it identifies the most promising planner for collision-free motion planning, being a valuable contribution for the inspection of maritime structures, as well as for the manipulation procedures of autonomous underwater vehicles during close range operations.