Dynamic Consensus of High-order Multi-agent Systems and Its Application in the Motion Control of Multiple Mobile Robots

In this paper, the leader-following consensus problem for multi-agent linear dynamic systems is considered. All agents and leader have identical multi-input multi-output （MIMO） linear dynamics that can be of any order, and only the output information of each agent is delivered throughout the communication network. When the interaction topology is fixed, the leader-following consensus is attained by Ho~ dynamic output feedback control, and the sufficient condition of robust controllers is equal to the solvability of linear matrix inequality （LMI）. The whole analysis is based on spectral decomposition and an equivalent decoupled structure achieved, and the stability of the system is proved. Finally, we extended the theoretical results to the case that the interaction topology is switching. The simulation results for multiple mobile robots show the effectiveness of the devised methods.

Path Planning of the Multiple Mobile Robot System Applied in Chinese Chess Game

The article presents the path planning algorithm to be applied in the Chinese chess game, and uses multiple mobile robots to present the experimental scenario. Users play the Chinese chess game using the mouse on the supervised computer. The supervised computer programs the motion paths using A＊ searching algorithm, and controls mobile robots moving on the grid based chessboard platform via wireless radio frequency （RF） interface. The A＊ searching algorithm solves shortest path problems of mobile robots from the start point to the target point, and avoids the obstacles on the chessboard platform. The supervised computer calculates the total time to play the game, and computes the residual time to play chess in the step for each player. The simulation results can fired out the shortest motion paths of the mobile robots （chesses） moving to target points from start points in the monitor, and decides the motion path to be existence or not. The eaten chess can moves to the assigned position, and uses the A＊ searching algorithm to program the motion path, too. Finally, the authors implement the simulation results on the chessboard platform using mobile robots. Users can play the Chinese chess game on the supervised computer according to the Chinese chess game rule, and play each step of the game in the assigned time. The supervised computer can suggests which player don＇t obey the rules of the game, and decides which player to be a winner. The scenario of the Chinese chess game feedback to the user interface using the image system.

Cooperative co-evolution based distributed path planning of multiple mobile robots

This paper proposes novel multiple-mobile-robot collision avoidance path planning based on cooperative co-evolution,which can be executed fully distributed and in parallel. A real valued co-evolutionary algorithm is developed to coordinate the movement of multiple robots in 2D world, avoiding C-space or grid net searching. The collision avoidance is achieved by cooperatively co-evolving segments of paths and the time interval to pass them. Methods for constraint handling, which are developed for evolutionary algorithm, make the path planning easier. The effectiveness of the algorithm is demonstrated on a number of 2Dpath planning problems.

Toward Coordination Control of Multiple Fish-Like Robots:Real-Time Vision-Based Pose Estimation and Tracking via Deep Neural Networks

Controlling multiple multi-joint fish-like robots has long captivated the attention of engineers and biologists,for which a fundamental but challenging topic is to robustly track the postures of the individuals in real time.This requires detecting multiple robots,estimating multi-joint postures,and tracking identities,as well as processing fast in real time.To the best of our knowledge,this challenge has not been tackled in the previous studies.In this paper,to precisely track the planar postures of multiple swimming multi-joint fish-like robots in real time,we propose a novel deep neural network-based method,named TAB-IOL.Its TAB part fuses the top-down and bottom-up approaches for vision-based pose estimation,while the IOL part with long short-term memory considers the motion constraints among joints for precise pose tracking.The satisfying performance of our TAB-IOL is verified by testing on a group of freely swimming fish-like robots in various scenarios with strong disturbances and by a deed comparison of accuracy,speed,and robustness with most state-of-the-art algorithms.Further,based on the precise pose estimation and tracking realized by our TAB-IOL,several formation control experiments are conducted for the group of fish-like robots.The results clearly demonstrate that our TAB-IOL lays a solid foundation for the coordination control of multiple fish-like robots in a real working environment.We believe our proposed method will facilitate the growth and development of related fields.

MOTION PLANNING OF MULTIPLE MOBILE ROBOTS COOPERATIVELY TRANSPORTING A COMMON OBJECT

Many applications above the capability of a single robot need the cooperation of multiple mobile robots, but effective cooperation is hard to achieve. In this paper, a master slave method is proposed to control the motions of multiple mobile robots that cooperatively transport a common object from a start point to a goal point. A noholonomic kinematic model to constrain the motions of multiple mobile robots is built in order to achieve cooperative motions of them, and a “Dynamic Coordinator” strategy is used to deal with the collision avoidance of the master robot and slave robot individually. Simulation results show the robustness and effectiveness of the method.

A Self-Position Estimation Algorithm for Multiple Mobile Robots Using Two Omnidirectional Cameras and an Accelerometer

This paper proposes a self-position estimate algorithm for the multiple mobile robots; each robot uses two omnidirectional cameras and an accelerometer. In recent years, the Great East Japan Earthquake and large-scale disasters have occurred frequently in Japan. From this, development of the searching robot which supports the rescue team to perform a relief activity at a large-scale disaster is indispensable. Then, this research has developed the searching robot group system with two or more mobile robots. In this research, the searching robot equips with two omnidirectional cameras and an accelerometer. In order to perform distance measurement using two omnidirectional cameras, each parameter of an omnidirectional camera and the position and posture between two omnidirectional cameras have to be calibrated in advance. If there are few mobile robots, the calibration time of each omnidirectional camera does not pose a problem. However, if the calibration is separately performed when using two or more robots in a disaster site, etc., it will take huge calibration time. Then, this paper proposed the algorithm which estimates a mobile robot＇s position and the parameter of the position and posture between two omnidirectional cameras simultaneously. The algorithm proposed in this paper extended Nonlinear Transformation （NLT） Method. This paper conducted the simulation experiment to check the validity of the proposed algorithm. In some simulation experiments, one mobile robot moves and observes the circumference of another mobile robot which has stopped at a certain place. This paper verified whether the mobile robot can estimate position using the measurement value when the number of observation times becomes 10 times in n/18 of observation intervals. The result of the simulation shows the effectiveness of the algorithm.

A Stochastic Approach for Cooperative Position Estimation of Multiple Mobile Robots

This paper proposes the cooperative position estimation of a group of mobile robots, which pertbrms disaster relief tasks in a wide area. When searching the wide area, it becomes important to know a robot＇s position correctly. However, for each mobile robot, it is impossible to know its own position correctly. Therefore, each mobile robot estimates its position from the data of sensor equipped on it. Generally, the sensor data is incorrect since there is sensor noise, etc. This research considers two types of the sensor data errors from omnidirectional camera. One is the error of white noise of the image captured by omnidirectional camera and so on. Another is the error of position and posture between two omnidirectional cameras. To solve the error of latter case, we proposed a self-position estimation algorithm for multiple mobile robots using two omnidirectional cameras and an accelerometer. On the other hand, to solve the error of the former case, this paper proposed an algorithm of cooperative position estimation for multiple mobile robots. In this algorithm, each mobile robot uses two omnidirectional cameras to observe the surrounding mobile robot and get the relative position between mobile robots. Each mobile robot estimates its position with only measurement data of each other mobile robots. The algorithm is based on a Bayesian filtering. Simulations of the proposed cooperative position estimation algorithm for multiple mobile robots are performed. The results show that position estimation is possible by only using measurement value from each other robot.

Simultaneous Position Estimation and Omnidirectional Camera Parameter Calibration for Multiple Mobile Robots

This paper proposed an algorithm on simultaneous position estimation and calibration of omnidirectional camera parameters for a group of multiple mobile robots. It is aimed at developing of exploration and information gathering robotic system in unknown environment. Here, each mobile robot is not possible to know its own position. It can only estimate its own position by using the measurement value including white noise acquired by two omnidirectional cameras mounted on it. Each mobile robot is able to obtain the distance to those robots observed from the images of two omnidirectional cameras while making calibration during moving but not in advance. Simulation of three robots moving straightly shows the effectiveness of the proposed algorithm.

OPTIMAL DYNAMIC LOAD DISTRIBUTION OF MULTIPLE COOPERATING ROBOT MANIPULATORS

For the situation of multiple cooperating manipulators handling a single object,an equilibrium equation is presented in which the manipulator dynamics and control forces/torques are taken into account,and a expression is derived to allow the optimal dynamic load distribution of the combined system can be made.

Adaptive robust simultaneous stabilization of multiple nn-degree-of-freedom robot systems

In this paper,the adaptive robust simultaneous stabilization problem of uncertain multiple n-degree-of-freedom(n-DOF)robot systems is studied using the Hamiltonian function method,and the corresponding adaptive L2 controller is designed.First,we investigate the adaptive simultaneous stabilization problem of uncertain multiple n-DOF robot systems without external disturbance.Namely,the single uncertain n-DOF robot system is transformed into an equivalent Hamiltonian form using the unified partial derivative operator(UP-DO)and potential energy shaping method,and then a high dimensional Hamiltonian system for multiple uncertain robot systems is obtained by applying augmented dimension technology,and a single output feedback controller is designed to ensure the simultaneous stabilization for the higher dimensional Hamiltonian system.On this basis,we further study the adaptive robust simultaneous stabilization control problem for the uncertain multiple n-DOF robot systems with external disturbances,and design an adaptive robust simultaneous stabilization controller.Finally,the simulation results show that the adaptive robust simultaneous stabilization controller designed in this paper is very effective in stabilizing multi-robot systems at the same time.

Cooperative transport strategy for formation control of multiple mobile robots

This paper addresses a box transport problem that requires the cooperation of multiple mobile robots. A geometric-based distributed formation control strategy is proposed for robots to push the box to the target, which might be static or dynamic. Velocity and hardware constraints are considered in the advanced planning of the trajectory. Information sharing is included because the robots used as box pushers cannot acquire the required environmental information from their local sensors. Simulation results show the effectiveness of the proposed distributed cooperation strategy.

Control strategy for multiple capsule robots in intestine

Based on the critical gap phenomenon of the intestinal capsule robot,a variable-diameter capsule robot with radial gap self-compensation is developed in this paper.With the functional variation principle,a fluid dynamic pressure model satisfying the boundary conditions of the outer surface of capsule robot with screw blades is derived.The critical gap phenomenon is studied theoretically and experimentally based on the end effect and the dynamic balance characteristics of the fluid on the surface of capsule robot.The concept of start-up rotation speed is defined,the relationship between the start-up rotation speed and the spiral parameters of capsule robot is investigated.The strategy for implementing drive and control on several capsule robots under the same rotational magnetic field is proposed,and by defining the start-up curves of several capsule robots with the similar motion regulation as the objective functions,genetic algorithm is employed to optimize the spiral parameters of several capsule robots.Experiments have shown that the proposed drive and control strategy for several capsule robots can be implemented effectively.It has a good prospect of application inside intestine to realize the drive and control on several capsule robots for different medical purposes.

Task Planning and Collaboration of Jellyfish-inspired Multiple Spherical Underwater Robots

Task planning and collaboration of multiple robots have broad application prospects and value in the field of robotics.To improve the performance and working efficiency of our Spherical Underwater Robot(SUR),we propose a multi-robot control strategy that can realize the task planning and collaboration of multiple robots.To complete real-time information sharing of multiple robots,we first build an acoustic communication system with excellent communication performance under low noise ratio conditions.Then,the task planning and collaboration control strategy adjust the SURs so that they maintain their positions in the desired formation when the formation moves.Multiple SURs can move along desired trajectories in the expected formation.The control strategy of each SUR uses only its information and limited information of its neighboring SURs.Finally,based on theoretical analysis and experiments,we evaluate the validity and reliability of the proposed strategy.In comparison to the traditional leader–follower method,it is not necessary to designate a leader and its followers explicitly in our system;thus,important advantages,such as fault tolerance,are achieved.

Formation Feedback Applied to Behavior-Based Approach to Formation Keeping

Approaches to the study of formation keeping for multiple mobile robots are analyzed and a behavior-based robot model is built in this paper. And, a kind of coordination architecture is presented, which is similar to the infantry squad organization and is used to realize multiple mobile robots to keep formations. Simulations verify the validity of the approach to keep formation, which combines the behavior-based method and formation feedback. The effects of formation feedback on the performance of the system are analyzed.