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.

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.

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.

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.

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.

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.

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.

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.