Satellite-Based Tele-Operation of an Underwater Vehicle-Manipulator System. Preliminary Experimental 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

Control of Redundant Robots Under Hard Joint Constraints: Saturation in the Null Space

We present an efficient method for addressing online the inversion of differential task kinematics for redundant manipulators, in the presence of hard limits on joint space motion that can never be violated. The proposed SNS (Saturation in the Null Space) algorithm proceeds by successively discarding the use of joints that would exceed their motion bounds when using the minimum norm solution. When processing multiple tasks with priority, the SNS method realizes a preemptive strategy by preserving the correct order of priority in spite of the presence of saturations. In the single- and multi-task case, the algorithm automatically integrates a least possible task scaling procedure, when an original task is found to be unfeasible. The optimality properties of the SNS algorithm are analyzed by considering an associated Quadratic Programming problem. Its solution leads to a variant of the algorithm, which guarantees optimality also when the basic SNS algorithm does not. Numerically efficient versions of these algorithms are proposed. Their performance allows real-time control of robots executing many prioritized tasks with a large number of hard bounds. Experimental results are reported

ROBUST project: Control Framework for Deep Sea Mining Exploration

This paper presents the control framework under development within the ROBUST Horizon 2020 project, whose goal is the development of an autonomous robotic system for the exploration of deep-sea mining sites. After a bathymetric survey of the initial zone of interest, the robotized system selects a subarea deemed to have the most chances of containing a manganese nodule field and proceeds with a detailed low altitude survey. Whenever a possible nodule is found, it performs an insitu measurement through laser induced spectroscopy. To do so, the underwater vehicle must first land on the seafloor, with a certain precision to allow a subsequent fixed-based manipulation, bringing its manipulator endowed with the laser system in the position to carry out the measurement. The work reports the developed control architecture and the simulation results supporting it

A Novel Practical Technique to Integrate Inequality Control Objectives and Task Transitions in Priority Based Control

The task priority based control is a formalism which allows to create complex control laws with nice invariance properties, i.e. lower priority tasks do not affect the execution of higher priority ones. However, the classical task priority framework (Siciliano and Slotine) lacked the ability of enabling and disabling tasks without causing discontinuities. Furthermore, tasks corresponding to inequality control objectives could not be efficiently represented within that framework. In this paper we present a novel technique to integrate both the activation and deactivation of tasks and the inequality control objectives in the priority based control. The technique, called iCAT (inequality control objectives, activations and transitions) task priority framework, exploits novel regularization methods to activate and deactivate any row of a given task in a prioritized hierarchy without incurring in practical discontinuities, while maintaining as much as possible the invariance properties of the other active tasks. Finally, as opposed to other techniques, the proposed approach has a linear cost in the number of tasks. Simulations, experimental results and a time analysis are presented to support the proposed technique

Robotized underwater interventions

Working in underwater environments poses many challenges for robotic systems. One of them is the low bandwidth and high latency of underwater acoustic communications, which limits the possibility of interaction with submerged robots. One solution is to have a tether cable to enable high speed and low latency communications, but that requires a support vessel and increases costs. For that reason, autonomous underwater robots are a very interesting solution. Several research projects have demonstrated autonomy capabilities of Underwater Vehicle Manipulator Systems (UVMS) in performing basic manipulation tasks, and, moving a step further, this chapter will present a unifying architecture for the control of an UVMS, comprehensive of all the control objectives that an UVMS should take into account, their different priorities and the typical mission phases that an UVMS has to tackle. The proposed strategy is supported both by a complete simulated execution of a test-case mission and experimental results

Behavioral control of unmanned aerial vehicle manipulator systems

In this paper a behavioral control framework is developed to control an unmanned aerial vehicle-manipulator (UAVM) system, composed by a multirotor aerial vehicle equipped with a robotic arm. The goal is to ensure vehicle-arm coordination and manage complex multi-task missions, where different behaviors must be encompassed in a clear and meaningful way. In detail, a control scheme, based on the null space-based behavioral paradigm, is proposed to handle the coordination between the arm and vehicle motion. To this aim, a set of basic functionalities (elementary behaviors) are designed and combined in a given priority order, in order to attain more complex tasks (compound behaviors). A supervisor is in charge of switching between the compound behaviors according to the mission needs and the sensory feedback. The method is validated on a real testbed, consisting of a multirotor aircraft with an attached 6 Degree of Freedoms manipulator, developed within the EU-funded project ARCAS (Aerial Robotics Cooperative Assembly System). At the the best of authors’ knowledge, this is the first time that an UAVM system is experimentally tested in the execution of complex multi-task missions. The results show that, by properly designing a set of compound behaviors and a supervisor, vehicle-arm coordination in complex missions can be effectively managed

Autonomous Underwater Intervention: Experimental Results of the MARIS Project

open11noopenSimetti, E. ;Wanderlingh, F. ;Torelli, S. ;Bibuli, M. ;Odetti, A. ;Bruzzone, G. ; Lodi Rizzini, D. ;Aleotti, J. ;Palli, G. ;Moriello, L. ;Scarcia, U.Simetti, E.; Wanderlingh, F.; Torelli, S.; Bibuli, M.; Odetti, Angelo; Bruzzone, G.; Lodi Rizzini, D.; Aleotti, J.; Palli, G.; Moriello, L.; Scarcia, U