Many operations performed by work class Remotely Operated Vehicles (ROVs) require the manipulation of heavy loads. An example is the manipulation and grouting of armour stones. A way to increase the working capabilities of the ROV is to introduce cables among the set of actuators. The cable lengths and tensions are controlled by winches placed on the vehicle. Being similar to a cable-driven parallel robot (CDPR), the resultant system inherits some advantages such as the possibility to generate large forces over a large workspace and the possibility to use CDPR techniques to estimate the pose of the ROV. This paper proposes a complete control architecture for the Hybrid Cable-Thruster actuated ROV (HCT-ROV) and analyzes, in computer simulations, the performances of such a system while it performs real world operations, such as heavy lifting and hovering in presence of water current.

In this article, we propose FlexHRC+, a hierarchical human-robot cooperation architecture designed to provide collaborative robots with an extended degree of autonomy when supporting human operators in high-variability shop-floor tasks. The architecture encompasses three levels, namely for perception, representation, and action. Building up on previous work, here we focus on an in-the-loop decision-making process for the operations of collaborative robots coping with the variability of actions carried out by human operators, and the representation level, integrating a hierarchical and/or graph whose online behavior is formally specified using first-order logic. The architecture is accompanied by experiments including collaborative furniture assembly and object positioning tasks.

This paper presents the control and perception framework used in the ROBUST EU Horizon 2020 project, aimed at integrate different technologies for developing an underwater autonomous robotic system for exploring deep-sea mining sites. The vehicle firstly collects data of the initial zone of interest and it selects a sub area which is the most probable to contain a manganese nodule field; then it carries out a low altitude survey. When a possible nodule is detected by the cameras, the vehicle lands on the seafloor, allowing the following fixed based manipulation which is designed to perform the nodule analysis. The work reports the implemented control and perception architecture and the preliminary pool experiments results.

Within the European project DexROV the topic of underwater intervention is addressed. In particular, a remote control room is connected through a satellite communication link to surface vessel, which is in turn connected to an UVMS (Underwater Vehicle-Manipulator System) with an umbilical cable. The operator may interact with the system using a joystick or exoskeleton. Since a direct teleoperation is not feasible, a cognitive engine is in charge of handling communication latency or interruptions caused by the satellite link, and the UVMS should have sufficient autonomy in dealing with low level constraints or secondary objectives. To this purpose, a task-priority-based inverse kinematics algorithm has been developed in order to allow the operator to control only the end effector, while the algorithm is in charge of handling both operative and joint-space constraints. This paper describes some preliminary experimental results achieved during the DexROV campaign of July 2017 in Marseilles (France), where most of the components have been successfully integrated and the inverse kinematics nicely run.

Modern manufacturing paradigms introduce the need for robots able to naturally cooperate with humans in an unstructured and dynamic environment. In this article we extend FlexHRC, an architecture for flexible and collaborative manufacturing robots, with an online perception-simulation-planning framework that allows the robot to assess the status of the workspace, keeping track at all times of the stage at which the cooperative manufacturing process is, to identify its next action, to simulate it to check its feasibility and, as a consequence, to dynamically allocate tasks to itself or the human operator. We have tested the FlexHRC with a dual-arm manipulator cooperating with a person to assemble a table with one tabletop and four legs.

In this paper we present a novel co-operative control policy purely for the transportation of large objects in underwater environments using two free floating vehicles, each one endowed with a 7 d.o.f redundant manipulator. Due to the presence of harsh conditions in underwater scenarios, it is extremely important to realize algorithms that depend on a minimal amount of explicit information exchanged by the agent, or without any exchange of information at all. To achieve this goal the control policy proposed in the paper only requires the exchange of six numbers at each time instant, while however exhibiting extremely good performances, inspite of the restraints on the information exchange.

The need for actual autonomy in underwater robotic systems is rapidly increasing. Many challenging issues derive from such a trend, one in all the requirement of coordinately controlling the motion of an underwater floating I-AUV endowing a robotic arm, to accomplish complex manipulation tasks. This work is aimed to present a strategy based on the prioritization of tasks of equality and inequality type, once combined with Dynamic Programming techniques, for coordinately controlling the motion of such I-AUV. A general algorithmic framework is developed and simulative results supporting its resulting effectiveness are presented.