A Client-server Oriented Programming Language For Autonomous Underwater Manipulation Available to Purchase

The most common obstacle that an autonomous underwater manipulation system must face is the low communication bandwidth and significant time delay inherent in acoustic subsea communication, which makes it very difficult to remotely operate the manipulator. Robot teleprogramming was proposed as an intermediate solution between supervised control systems and direct teleoperation when a significant delay appears in the communication. The main idea is to make the operator feel the system as a common teleoperation without the communication delay. It decouples the local and remote zones, by limiting the data exchange to a few symbolic information, as opposed to the common robot teleoperation system that uses low level information (e.g. the joint position, motor velocity reference, etc.). Another useful concept is semi-autonomous operation when significant communication delays exist. The user may provide higher level commands during a particular mission, instead of directly operating the manipulator,. It is an interesting concept between the fully autonomous mode and the classic teleoperation mode. In this approach, the function of the operator is to decide, after an analysis of the data, which particular task the vehicle is ready to execute and successively send the decision command. The low-level control commands are provided by a pre-programmed onboard subsystem. In this paper we describe a robot programming language developed in order to address the above issue. The language, suitable for real-time embedded control systems, offers at the same time flexibility, good performance and simplicity in describing a generic complex task. Its layer abstraction approach allows an easy adaptation to the hardware-specific requirements of different platforms. The last is an important distinctiveness from most of the currently available robot programming languages. The procedural approach has been chosen in order to enhance the performance while maintaining the flexibility required for executing complex tasks.