Dynamic Control of Mobile Multirobot Systems: The Cluster Space Formulation

The formation control technique called cluster space control promotes simplified specification and monitoring of the motion of mobile multirobot systems of limited size. Previous paper has established the conceptual foundation of this approach and has experimentally verified and validated its use for various systems implementing kinematic controllers. In this paper, we briefly review the definition of the cluster space framework and introduce a new cluster space dynamic model. This model represents the dynamics of the formation as a whole as a function of the dynamics of the member robots. Given this model, generalized cluster space forces can be applied to the formation, and a Jacobian transpose controller can be implemented to transform cluster space compensation forces into robot-level forces to be applied to the robots in the formation. Then, a nonlinear model-based partition controller is proposed. This controller cancels out the formation dynamics and effectively decouples the cluster space variables. Computer simulations and experimental results using three autonomous surface vessels and four land rovers show the effectiveness of the approach. Finally, sensitivity to errors in the estimation of cluster model parameters is analyzed.Fil: Mas, Ignacio Agustin. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Kitts, Christopher. Santa Clara University; Estados Unido

Optimization of Potential Field Method Parameters through networks for Swarm Cooperative Manipulation Tasks

An interesting current research field related to autonomous robots is mobile manipulation performed by cooperating robots (in terrestrial, aerial and underwater environments). Focusing on the underwater scenario, cooperative manipulation of Intervention-Autonomous Underwater Vehicles (I-AUVs) is a complex and difficult application compared with the terrestrial or aerial ones because of many technical issues, such as underwater localization and limited communication. A decentralized approach for cooperative mobile manipulation of I-AUVs based on Artificial Neural Networks (ANNs) is proposed in this article. This strategy exploits the potential field method; a multi-layer control structure is developed to manage the coordination of the swarm, the guidance and navigation of I-AUVs and the manipulation task. In the article, this new strategy has been implemented in the simulation environment, simulating the transportation of an object. This object is moved along a desired trajectory in an unknown environment and it is transported by four underwater mobile robots, each one provided with a seven-degrees-of-freedom robotic arm. The simulation results are optimized thanks to the ANNs used for the potentials tuning

Numerical Efficiency of Inverse Simulation Methods Applied to a Wheeled Rover

Extending the navigational capability of planetary rovers is essential for increasing the scientific outputs from such exploratory missions. In this paper a navigation method based on Inverse Simulation is applied to a four wheel rover. The method calculates the required control inputs to achieve a desired, specified response. Here this is a desired trajectory defined as a series of waypoints. Inverse Simulation considers the complete system dynamics of the rover to calculate the control input using an iterative, numerical Newton - Raphson scheme. The paper provides an insight into the numerical parameters that affect the performance of the method. Also, the influence of varying the timestep and the convergence tolerance is examined in terms of the quality of the calculated control input and the resulting trajectory, as well as the execution time. From this analysis a set of parameters and recommendations to successfully apply Inverse Simulation to a rover is presented

A Unified Task Priority Control Framework Design for Autonomous Underwater Vehicles

In this thesis, we investigate the problem of bringing various behaviours of Autonomous Underwater Vehicles under a common control framework. Thereby, we propose a unified guidance and control framework for AUVs based on the task priority control approach. This incorporate various behaviors such as path following, terrain following, obstacle avoidance, as well as homing and docking to stationary and moving docking stations. The integration of homing and docking maneuvers into the task priority framework is thus a novel contribution of this thesis. This integration allows, for example, to execute homing maneuvers close to uneven seafloor or obstacles, ensuring the safety of the AUV by giving the highest priority to the safety tasks. Furthermore, the proposed approach tackles a wide range of scenarios without ad hoc solutions. Indeed, the proposed approach is well suited for both the emerging trend of resident AUVs, which stay underwater for a long period inside garage stations, exiting to perform inspection and maintenance missions and homing back to them, and for AUVs that are required to dock to moving stations such as surface vehicles, or towed docking stations. The proposed techniques are further studied in a simulation setting, taking into account the rich number of aforementioned scenarios

6-DoF Navigation Systems for Autonomous Underwater Vehicles

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