Intelligent vehicles sense their dynamics and the environment to make proper decisions. Some of this information are hard to be measured or need expensive sensors. This paper addresses the estimation of road grade angles, along with tire-ground interaction forces, in a delayed interconnected cascade observer structure. A new approach using a Two-Stage Extended Kalman Filter is proposed, allowing a robust simultaneous estimation of the slow and fast dynamics variables. Experimental data is used to validate the estimator.

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.

Addresses the issue of automatic hovering of an outdoor autonomous airship using image-based visual servoing. The hovering controller is designed using a full dynamic model of the airship, in a PD error feedback scheme, taking the visual signals as output and extracted from an on-board camera. The behavior and stability of the airship motion during the task execution and subjected to the wind disturbance is studied. The approach is finally validated in simulation using an accurate airship model.

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.

The development of an unmanned airship capable of autonomous flight over user-defined locations for aerial data and imagery acquisition is the objective of the AURORA project. One important mission problem is the flight path following of the vehicle through a set of pre-defined points at a given altitude and velocity. In this article, a path tracking error generation methodology is presented and two different strategies for the guidance problem, one based on a H/sub /spl infin// control technique and another based on a PI control, are proposed and compared through a simulated case study.

Development of reliable control systems for semi-autonomous unmanned aerial vehicles require the use of extensive simulation data provided by an accurate six-degrees-of-freedom dynamic model. In this article we describe a Simulink-based control system development environment for Project AURORA's unmanned robotic airship, as well as the control algorithms and supervisory level of AURORA's control system. A complete take-off to landing mission illustrates the utilization of this environment.

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.

This paper discusses Project AURORA (autonomous unmanned remote monitoring robotic airship) which focuses on the development of the control, navigation, sensing, and inference technologies required for substantially autonomous robotic airships. Our target application areas include the use of robotic airships for environmental, biodiversity, and climate research and monitoring. Based on typical mission requirements, we present arguments that favour airships over airplanes and helicopters as the ideal platforms for such missions. We outline the overall system architecture of the AURORA robotic airship, discuss its main subsystems, and mention the research and development issues involved.