ChoiRbot: A ROS 2 Toolbox for Cooperative Robotics

In this letter, we introduce ChoiRbot, a toolbox for distributed cooperative robotics based on the novel Robot Operating System (ROS) 2. ChoiRbot provides a fully-functional toolset to execute complex distributed multi-robot tasks, either in simulation or experimentally, with a particular focus on networks of heterogeneous robots without a central coordinator. Thanks to its modular structure, ChoiRbot allows for a highly straight implementation of optimization-based distributed control schemes, such as distributed optimal control, model predictive control, task assignment, in which local computation and communication with neighboring robots are alternated. To this end, the toolbox provides functionalities for the solution of distributed optimization problems. The package can be also used to implement distributed feedback laws that do not need optimization features but do require the exchange of information among robots. The potential of the toolbox is illustrated with simulations and experiments on distributed robotics scenarios with mobile ground robots. The ChoiRbot toolbox is available at https://github.com/OPT4SMART/choirbot

Implementation of Distributed Time Exchange Based Cooperative Forwarding

In this paper, we design and implement time exchange (TE) based cooperative forwarding where nodes use transmission time slots as incentives for relaying. We focus on distributed joint time slot exchange and relay selection in the sum goodput maximization of the overall network. We formulate the design objective as a mixed integer nonlinear programming (MINLP) problem and provide a polynomial time distributed solution of the MINLP. We implement the designed algorithm in the software defined radio enabled USRP nodes of the ORBIT indoor wireless testbed. The ORBIT grid is used as a global control plane for exchange of control information between the USRP nodes. Experimental results suggest that TE can significantly increase the sum goodput of the network. We also demonstrate the performance of a goodput optimization algorithm that is proportionally fair.Comment: Accepted in 2012 Military Communications Conferenc

Networked cooperation-based distributed model predictive control using Laguerre functions for large-scale systems

International audienceThis paper proposes a novel cooperative distributed control system architecture based on unsupervised and independent Model Predictive Control (MPC) using discrete-time Laguerre functions to improve the performance of the whole system. In this distributed framework, local MPCs algorithms might exchange and require information from other sub-controllers via the communication network to achieve their task in a cooperative way. In order to reduce the computational burden in the local rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are used to approximate the predicted control trajectory. Simulation results show that the proposed architecture could guarantee satisfactory global performance even under strong interactions among the subsystems

Cooperative distributed MPC for tracking

This paper proposes a cooperative distributed linear model predictive control (MPC) strategy for tracking changing setpoints, applicable to any finite number of subsystems. The proposed controller is able to drive the whole system to any admissible setpoint in an admissible way, ensuring feasibility under any change of setpoint. It also provides a larger domain of attraction than standard distributed MPC for regulation, due to the particular terminal constraint. Moreover, the controller ensures convergence to the centralized optimum, even in the case of coupled constraints. This is possible thanks to the warm start used to initialize the optimization Algorithm, and to the design of the cost function, which integrates a Steady-State Target Optimizer (SSTO). The controller is applied to a real four-tank plant