Bottom-Following for Remotely Operated Vehicles: Algorithms and Experiments

Abstract

This paper addresses the problem of designing high precision bottom followers for remotely operated vehicles. In the framework of hierarchical control architectures able to uncouple the robot's kinematics (guidance) and dynamics (velocity control), the task of bottom-following is accomplished by suitable guidance task functions, which enable the system to handle unmodeled, i.e., not measured or estimated, kinematics interactions between the robot and the operating environment. In order to increase the bottom followers' reliability, the paper discusses possible techniques for modeling and handling the environmental and measurement uncertainty in the estimate of the local interactions between the vehicle and the operating environment, i.e., altitude and bottom slope. In particular, according to at-sea operational experience, the problem of managing dropouts due to erroneous tracking of multi-path echoes by the ROV altimeter(s) is addressed. Results of a large set of pool trials carried out with the Romeo ROV are reported and discussed.