Rows of trees such as in orchards, planted in straight parallel lines can provide navigation cues for autonomous machines that operate in between them. When the tree canopies are well managed, tree rows appear similar to corridor walls and a simple 2D sensing scheme suffices. However, when the tree canopies are three dimensional, or ground vegetation occludes tree trunks, it is necessary to use a three dimensional sensing mode. An additional complication in prolific canopies is that GPS is not reliable and hence is not suitable to register data from sensors onboard a traversing vehicle. Here, we present a method to register 3D data from a lidar sensor onboard a vehicle that must accurately determine its pose relative to the rows. We first register point cloud into a common reference frame and then determine the position of tree rows and trunks in the vicinity to determine the vehicle pose. Our method is tested online and with data from commercial orchards. Experimental results show that the accuracy is sufficient to enable accurate traversal between tree rows even when tree canopies do not approximate planar walls.

Internet robotic systems have a different role in the use and development of aerial robots compared to that for ground robots. While for ground robotic vehicles, Internet is useful for remote operation or to make remote development, in aerial vehicles, in addition, the safety aspect must be considered very carefully. This paper addresses the requirements to the specific case of Internet aerial robots. It describes the conceptual and implementation aspects of an Internet-based software architecture for the AURORA unmanned autonomous airship project, showing its use in the different project phases.

Project AURORA aims at the development of an unmanned airship capable of autonomous flight over user-defined locations for aerial inspection and imagery acquisition. In this article the authors report a successful autonomous flight achieved through a set of pre-defined points, one of the first of its kind in the literature. The guidance control strategy is based on a path tracking error generation methodology that takes into account both the distance and the angular errors of the airship with respect to the desired trajectory. The control strategy uses a PI controller for the tail surfaces' deflection.

We present one of the first Internet-accessible airship simulators, based on a comprehensive airship dynamic model. The simulator is meant to be used as a tool for the development of control and navigation methods for autonomous and semi-autonomous robotic airships and as testbed for airship pilot training. Realistic views of both the airship in flight and that of a virtual pilot are provided, as are commands to apply thrust to the engines, swivel them up and down, and deflect the control surfaces. This work is significant for providing robotics researchers with means to safely experiment with airship control.