Coordination Of Multiple Mobile Robots Research Articles

Distributed Receding Horizon Coverage Control for Multiple Mobile Robots

This paper presents a distributed coverage control scheme based on receding horizon control for the coordination of multiple mobile robots to cover an event. The mission space is modeled using a probability density function representing the probability of occurrence of events. The distributed scheme is generated by the decomposition of a single optimal coverage problem into distributed receding horizon coverage control problems, each of them associated with one robot. The distributed coverage scheme is proven to optimally stabilize robots at a centroidal Voronoi configuration, which is an optimal configuration to cover an event. The control scheme is tested in three simulation environments to illustrate its good performance at environments with any probability density function of events, as well as its ability to generalize to much larger groups of mobile robots.

Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robots

In autonomous multirobot systems one of the concerns is how to prevent collisions between the individual robots. One approach to this problem involves finding coordinated trajectories from start to destination for all the robots and then letting the robots follow the preplanned coordinated trajectories. A widely used practical method for finding such coordinated trajectories is “classical” prioritized planning, where robots plan sequentially one after another. This method has been shown to be effective in practice, but it is incomplete (i.e., there are solvable problem instances that the algorithm fails to solve) and it has not yet been formally analyzed under what circumstances is the method guaranteed to succeed. Further, prioritized planning is a centralized algorithm, which makes the method unsuitable for decentralized multirobot systems.

適応的走行制御に基づいたロボット群の効果的な移動の実現

適応的走行制御に基づいたロボット群の効果的な移動の実現

Coordination of multiple mobile robots with limited communication range in pursuit of single mobile target in cluttered environment

This paper addresses the problem of coordinating multiple mobile robots in searching for and capturing a mobile target, with the aim of reducing the capture time. Compared with the previous algorithms, we assume that the target can be detected by any robot and captured successfully by two or more robots. In this paper, we assume that each robot has a limited communication range. We maintain the robots within a mobile network to guarantee the successful capture. In addition, the motion of the target is modeled and incorporated into directing the motion of the robots to reduce the capture time. A coordination algorithm considering both aspects is proposed. This algorithm can greatly reduce the expected time of capturing the mobile target. Finally, we validate the algorithm by the simulations and experiments.

Formation path following control of unicycle-type mobile robots

This paper presents a control strategy for the coordination of multiple mobile robots. A combination of the virtual structure and path following approaches is used to derive the formation architecture. A formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. The approach is then extended to consider the formation controller by taking into account the physical dimensions and dynamics of the robots. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robot’s motion. Simulation results with three robots are included to show the performance of our control system. Finally, the theoretical results are experimentally validated on a multi-robot platform.

Distributed Constraint Force Approach for Coordination of Multiple Mobile Robots

A new approach to coordination of multiple mobile robots is presented in this paper. The approach relies on the notion of constraint forces which are used in the development of the dynamics of a system of constrained particles with inertia. A familiar class of dynamic, nonholonomic robots are considered. The goal is to design a distributed coordination control algorithm for each robot in the group to achieve, and maintain, a particular formation while ensuring navigation of the group. The theory of constraint forces is used to generate a stable control algorithm for each mobile robot that will achieve, and maintain, a given formation. The advantage of the proposed method is that the formation keeping forces (constraint forces) cancel only those applied forces which act against the constraints. Another feature of the proposed distributed control algorithm is that it allows to add/remove other mobile robots into/from the formation gracefully with simple modifications of the control input. Further, the algorithm is scalable. To corroborate the theoretical approach, simulation results on a group of six robots are shown and discussed.

A Distributed Constraint Force Approach for Coordination of Multiple Mobile Robots

A new approach to coordination of multiple mobile robots is presented in this paper. The approach relies on the notion of constraint forces which are used in the development of the dynamics of a system of constrained particles with inertia. A familiar class of dynamic, nonholonomic robots are considered. The goal is to design a distributed coordination control algorithm for each robot in the group to achieve, and maintain, a particular formation while ensuring navigation of the group. The theory of constraint forces is used to generate a stable control algorithm for each mobile robot that will achieve, and maintain, a given formation. The advantage of the proposed method is that the formation keeping forces (constraint forces) cancel only those applied forces which act against the constraints. Another feature of the proposed distributed control algorithm is that it allows to add/remove other mobile robots into/from the formation gracefully with simple modifications of the control input. Further, the algorithm is scalable. To corroborate the theoretical approach, simulation results on a group of six robots are shown and discussed.