Abstract — Rivers with heavy vegetation are hard to map from the air. Here we consider the task of mapping their course and the vegetation along the shores with the specific intent of determining river width and canopy height. A complication in such riverine environments is that only intermittent GPS may be available depending on the thickness of the surrounding canopy. We present a multimodal perception system to be used for the active exploration and mapping of a river from a small rotorcraft flying a few meters above the water. We describe three key components that use computer vision, laser scanning, and inertial sensing to follow the river without the use of a prior map, estimate motion of the rotorcraft, ensure collisionfree operation, and create a three dimensional representation of the riverine environment. While the ability to fly simplifies the navigation problem, it also introduces an additional set of constraints in terms of size, weight and power. Hence, our solutions are cognizant of the need to perform multi-kilometer missions with a small payload. We present experimental results along a 2km loop of river using a surrogate system. I.

Simultaneous localization and mapping (SLAM) has been shown to be feasible in many small, two-dimensional, structured domains. The next challenge is to develop real-time SLAM methods that enable robots to explore large, three-dimensional, unstructured environments and allow subsequent operation in these environments over long periods of time. To circumvent the scale limitations inherent in SLAM, the world can be divided up into more manageable pieces. SLAM can be formulated on these pieces by using a combination of metric submaps and a topological map of the relationships between submaps. The contribution of this paper is a realtime, three-dimensional SLAM approach that combines an evidence grid–based volumetric submap representation, a robust Rao–Blackwellized particle filter, and a topologically flexible submap segmentation framework and map representation. We present heuristic methods for deciding how to segment the world and for reconstructing large-scale metric maps for the purpose of closing loops. We demonstrate our method on a mobile robotic platform operating in large, three-dimensional environments. C ○ 2009 Wiley Periodicals, Inc. 1.

Abstract Accurately mapping the course and vegetation along a river is challenging, since overhanging trees block GPS at ground level and occlude the shore line when viewed from higher altitudes. We present a multimodal perception system for the active exploration and mapping of a river from a small rotorcraft. We describe three key components that use computer vision, laser scanning, inertial sensing and intermittant GPS to estimate the motion of the rotorcraft, detect the river without a prior map, and create a 3D map of the riverine environment. Our hardware and software approach is cognizant of the need to perform multi-kilometer missions below tree level with size, weight and power constraints. We present experimental results along a 2 km loop of river using a surrogate perception payload. Overall we can build an