Robot Formation Research Articles

Xenobots

Technology is improving day by day and every new face of it is engrossing, making applied science astonishment. Robotics and Artificial Intelligence have taken the world beyond automation. Automation was once considered as a challenge, but now the same technology has stunned the whole world, with the transformation of vision to the reality of live cell robots. In this modern era, evolutionary algorithms with Artificial Intelligence have made an impact on the automation and the creation of rare live-cell species by integrating biological aspects of frog cells. It would be thus useful in various domains to build technologies using self-renewing, and biocompatible materials of which the ideal candidates are living themselves. Thus, this paper presents a live cell robot named Xenobots, its design method, formation, applications, and transformation of live cell robots to humanoid robots that mimic the human brain.

Time-Optimal Velocity Tracking Control for Consensus Formation of Multiple Nonholonomic Mobile Robots.

The problem of velocity tracking is considered essential in the consensus of multi-wheeled mobile robot systems to minimise the total operating time and enhance the system’s energy efficiency. This study presents a novel switched-system approach, consisting of bang-bang control and consensus formation algorithms, to address the problem of time-optimal velocity tracking of multiple wheeled mobile robots with nonholonomic constraints. This effort aims to achieve the desired velocity formation in the least time for any initial velocity conditions in a multiple mobile robot system. The main findings of this study are as follows: (i) by deriving the equation of motion along the specified path, the motor’s extremal conditions for a time-optimal trajectory are introduced; (ii) utilising a general consensus formation algorithm, the desired velocity formation is achieved; (iii) applying the Pontryagin Maximum Principle, the new switching formation matrix of weights is obtained. Using this new switching matrix of weights guarantees that at least one of the system’s motors, of either the followers or the leader, reaches its maximum or minimum value by using extremals, which enables the multi-robot system to reach the velocity formation in the least time. The proposed approach is verified in a theoretical analysis along with the numerical simulation process. The simulation results demonstrated that using the proposed switched system, the time-optimal consensus algorithm behaved very well in the networks with different numbers of robots and different topology conditions. The required time for the consensus formation is dramatically reduced, which is very promising. The findings of this work could be extended to and beneficial for any multi-wheeled mobile robot system.

Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

Mobile robots are widely used in many applications, while various types of mobile robots and their control researches have been proposed in literature. Since swarm robots have higher flexibility and capacity for teamwork, this paper presents a grey estimator-based tracking controller for formation trajectory tracking of swarm robots. First, wheel-type mobile robots are used and modeled for the controller design. Then, a grey dynamic estimator is developed to estimate the environmental disturbance and model uncertainty for linear feedback compensation. As a result, the asymptotic trajectory tracking is assured, so that the application on the swarm robot formation is achieved for a multi-agent system. The computational complexity is slightly reduced by the design. Finally, in order to verify the reliability of swarm robot formation, several types of formation are maintained by the grey estimator-based feedback linearization controller.

Shared Control of an Aerial Cooperative Transportation System with a Cable-suspended Payload

This paper presents a novel bilateral shared framework for a cooperative aerial transportation and manipulation system composed by a team of micro aerial vehicles with a cable-suspended payload. The human operator is in charge of steering the payload and he/she can also change online the desired shape of the formation of robots. At the same time, an obstacle avoidance algorithm is in charge of avoiding collisions with the static environment. The signals from the user and from the obstacle avoidance are blended together in the trajectory generation module, by means of a tracking controller and a filter called dynamic input boundary (DIB). The DIB filters out the directions of motions that would bring the system too close to singularities, according to a suitable metric. The loop with the user is finally closed with a force feedback that is informative of the mismatch between the operator’s commands and the trajectory of the payload. This feedback intuitively increases the user’s awareness of obstacles or configurations of the system that are close to singularities. The proposed framework is validated by means of realistic hardware-in-the-loop simulations with a person operating the system via a force-feedback haptic interface.

Event‐triggered control for bipartite consensus and formation of multiple wheeled mobile robots with non‐holonomic constraint

AbstractThis paper studies the event‐triggered control scheme to tackle the position centroid bipartite consensus/formation problems of multiple wheeled mobile robots with non‐holonomic constraint. Based on a reversible input conversion, the dynamics of the reference positions of robots are described as two teams of first‐order integrators. The event‐triggered control input and the event‐triggering condition are constructed, ensuring that the position of each robot converges to the initial bipartite centroid location while their orientations and velocities reach some constants and zero, respectively. Moreover, we exclude the possibility of Zeno behavior. Subsequently, the proposed event‐triggered control mechanism is expanded to drive all robots to meet at the expected geometric pattern centred at the initial bipartite centroid. At last, simulations are given to validate the effectiveness of the provided theoretical strategy.

Dual Quaternion Cluster-Space Formation Control

We present a tracking controller for mobile multi-robot systems based on dual quaternion pose representations applied to formations of robots in a leader-follower configuration, by using a cluster-space state approach. The proposed controller improves system performance with respect to previous works by reducing steady-state tracking errors. The performance is evaluated through experimental field tests with a formation of an unmanned ground vehicle (UGV) and an unmanned aerial vehicle (UAV), as well as a formation of two UAVs.

Adaptive Secure Control for Leader-Follower Formation of Nonholonomic Mobile Robots in the Presence of Uncertainty and Deception Attacks

This paper addresses an adaptive secure control problem for the leader-follower formation of nonholonomic mobile robots in the presence of uncertainty and deception attacks. It is assumed that the false data of the leader robot’s information attacked by the adversary is transmitted to the follower robot through the network, and the dynamic model of each robot has uncertainty, such as unknown nonlinearity and external disturbances. A robust, adaptive secure control strategy compensating for false data and uncertainty is developed to accomplish the desired formation of nonholonomic mobile robots. An adaptive compensation mechanism is derived to remove the effects of time-varying attack signals and system uncertainties in the proposed control scheme. Although unknown deception attacks are injected to the leader’s velocities and the model nonlinearities of robots are unknown, the boundedness and convergence of formation tracking errors of the proposed adaptive control system are analyzed in the Lyapunov sense. The validity of the proposed scheme is verified via simulation results.

Coordinated Movement of Multiple Robots in Outdoor Environment with Obstacles Pages

This article mainly focuses on the proposal of the program that coordinates the movement of multiple robots in outdoor environment. The emphasis of the proposed algorithm is on collision free movement. Simulation with four robots that are controlled in an environment with obstacles is the result of these experiments. The formation of robots consists of a leader and three following robots, which are trying to copy leader¢‚¬„¢s movement. Robots use GPS, laser rangefinder, as well as bumpers sensors for the environment scanning. GPS is used as positioning sensor and other sensors are used for reactive navigation. Besides that, simulation uses virtual reality from Microsoft Robotics Studio 4 (MRS). In addition, programming language used for this simulation is called Visual Programming Language. Advantage of MRS usage is that the final code can be simply transferred into real robots.

A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty

In this paper, a distributed predictive control with the model uncertainty which uses the data-driven strategy and robust theory (data-driven RDMPC) is proposed for the formation control of multiple mobile robots. The robust performance objective minimization is applied to replace the quadratic performance objective minimization to establish the optimization problem, where the model uncertainty is considered in the distributed system. The control policy is derived by applying the data-driven strategy, and the future predictive value is obtained by employing the linear law in the historical data. Lyapunov theory is referred to analyze the stability of the mobile robot formation system. The effectiveness of the proposed method is proved by a set of simulation experiments.

Methods of Formation Control for a Group of Mobile Robots (a Review)

The multi-robot formation control is an essential issue in robotics. This review focuses on important lines of research on current contr ol is s ues and s tr ateg ies on a g r oup of unmanned autonomous vehicles/r obots for mation. In this paper, we pr ovide a br ief description of each method characterizing its key benefits and drawbacks. A multilayered classification of both centralized and decentralized formation control methods is proposed. We consider the classification of robot communication topologies in terms of centralized control. Seminal works dedicated to the practical application of centralized approach are briefly discussed. The majority of centralized methodsare represented by a " leader-follower" approach, taking into account the robot’s dynamics models. Furthermore, the most common models of vehicle dynamics are mentioned. In the framework of decentralized approach, behaviour-based algorithms, as well as swarm algorithms, are discussed. Then, we present an outlook of both centralized and decentralized virtual structure methods used in robot formation control. The described modifications of these methods allow tracing the evolution of the virtual structure approach to hybrid algorithms used for cooperative movement of a group of robots. This paper deals with formation control approach considering communication delays and low carrying capacity in an inter-vehicular communication network as very few works discussed this issue despite its relevance. We pointed out the main development trends of formation control approaches. The most effective approach is the integration of various methods of the formation control so that their disadvantages are nullified. As the same time, the most common disadvantage of discussed formation control methods is their weak conceptual framework in terms of kinematic and dynamic constraints of robots.

РАЗРАБОТКА МНОГОУРОВНЕВОЙ СИСТЕМЫ ПЛАНИРОВАНИЯ ТРАЕКТОРИИ ДВИЖЕНИЯ ГРУППЫ АНПА В НЕИЗВЕСТНОЙ СРЕДЕ С ПРЕПЯТСТВИЯМИ

The article discusses the problem of organizing the group movement of marine robotics(MRS), in particular, unmanned autonomous underwater vehicles (AUV), in an a priori unknownenvironment with obstacles. A brief analysis of existing projects on the subject of MRS group control,and path-planning algorithms have been carried out. The presence of numerous studies inthis area confirms the relevance of the indicated problem. The formal statement of the problem ofthe movement of four robots in formation is presented. The proposed method for a group pathplanning is based on a combined approach that organizes a multi-level solution to organizing themovement of MRS. At the upper level, a system for global path planning and mission control wasdeveloped based on the random tree method, which provides the general movement of the groupbased on a priori information about the state of the environment. The lower-level planning systemadjusts the global path, allowing objects at the local level to carry out the group agents’ movementand interaction, including ensuring their collision-free movement in environment and exit from theareas of local minima. The article provides a detailed analytical description of the developed algorithmand a block diagram of its functioning. Numerical simulation of the movement of a groupof 4 AUVs in a non-deterministic environment with fixed obstacles is carried out. The simulationwas carried out taking into account obstacles of various shapes and complexity. The results ofmathematical modeling demonstrated the solution to the problem of the exit of the AUV groupfrom the area of the local minimum. Full-scale tests are presented on the example of a group ofthree unmanned boats: a group of mobile objects formed a formation and carried out a movementin a given formation to target positions and returned to the final zone. In addition, the local planningmodule developed within the framework of this article was integrated into the software of the"Shadow" underwater glider control system. In the conclusion, the results of the proposed methodand its further development, in particular, its application in 3D environment, are considered.

Pattern phase transitions in 3D minimal Vicsek model

A large part of biological collective behaviors involves motional formation patterns like migration, vortex, aggregation, etc., in three-dimensional space, but the phase transition principles among these patterns still remain a dilemma. In this letter, by tweaking the vision range of the particles in a minimal collective motion model, phase transitions are observed among gas-like, crystal-like, and liquid-sphere–like patterns. Significantly, the increase of noise magnitudes will destroy the moving direction synchronization of gas-like and crystal-like phases, but not the liquid-sphere–like phase. By contrast, three sub-phases of migration liquid-sphere, vortex liquid-sphere and aggregation liquid-sphere emerge by slightly increasing noise magnitudes. This study sheds some light onto the forming mechanisms of 3D motional patterns of abundant biological groups. These insights could be expected to enable tuning the collective motional formations of multi-unmanned systems or robots by simply tweaking a few dynamical parameters as well.

Speed Control for Leader-Follower Robot Formation Using Fuzzy System and Supervised Machine Learning.

Mobile robots are endeavoring toward full autonomy. To that end, wheeled mobile robots have to function under non-holonomic constraints and uncertainty derived by feedback sensors and/or internal dynamics. Speed control is one of the main and challenging objectives in the endeavor for efficient autonomous collision-free navigation. This paper proposes an intelligent technique for speed control of a wheeled mobile robot using a combination of fuzzy logic and supervised machine learning (SML). The technique is appropriate for flexible leader-follower formation control on straight paths where a follower robot maintains a safely varying distance from a leader robot. A fuzzy controller specifies the ultimate distance of the follower to the leader using the measurements obtained from two ultrasonic sensors. An SML algorithm estimates a proper speed for the follower based on the ultimate distance. Simulations demonstrated that the proposed technique appropriately adjusts the follower robot’s speed to maintain a flexible formation with the leader robot.

A Path-Following Controller for Guiding a Single Robot or a Multi-robot System

A solution to the problem of path-following by a team of terrestrial mobile robots is proposed in this paper. The proposal, in this case, is a formation controller dealing with three robots navigating in a coordinate way (as a formation). Based on the controller proposed to guide the formation to follow a prescribed path, an extension to the case of path-following with a single terrestrial mobile robot is also proposed. When regarding a formation of mobile robots, the proposed solution consists in applying a path-following controller to the center of mass of the formation, dealt with as a single virtual robot, and trajectory-tracking controllers to the individual robots in the formation. The advantage of such approach is that it allows planning the motion of the desired formation without specifying how each robot should move. The movement is specified for the formation as a whole, using a representation called cluster-space, and the movement of the individual robots is derived from the specification of the formation movement directly, using transformations from the cluster-space to the space of the robots and vice versa. In the sequel, the path-following controller designed for the virtual robot is analyzed in detail, now dealing with the possibility of being also used as a path-following controller applied to a single real robot. Theoretical stability analysis is presented, as well as some experimental results, whose analysis allows claiming that the proposed controller is suitable to guide either a single robot or a multi-robot formation when following a path.

Recent Advances in Formations of Multiple Robots

Recent Advances in Formations of Multiple Robots

Scaled consensus of second‐order multiagent systems via distributed adaptive control

AbstractThis article investigates scaled consensus of second‐order multiagent systems (MASs) via distributed adaptive control. Two distributed adaptive scaled consensus protocols are proposed. First, to solve the dynamic scaled consensus problem, based on the neighbors' position and velocity information, two time‐varying coupling gains are introduced into the node‐based distributed adaptive protocol. Second, static scaled consensus is discussed under another distributed adaptive algorithm. It is shown proposed scaled consensus protocols are flexible, which are able to solve standard consensus, group consensus, and bipartite consensus problems with specific scale values. Finally, two examples of robot formation with nine agents are given to verify the effectiveness of the theoretical analysis.

Time-varying Nonholonomic Robot Consensus Formation Using Model Predictive Based Protocol With Switching Topology

In this paper, for controlling the time-varying consensus formation (TVCF) of multiply nonholonomic robots under switching information transforming topology, a generalized consensus formation system, which is controlled by a neural-dynamic-optimized distributed model predictive control (NDMPC) based consensus protocol strategy, is developed. The system consists of an auxiliary consensus maneuvering subsystem and a formation tracking subsystem. Through simultaneously stabilizing the generalized errors consisted of these two subsystems under the switching topologies, the consensus object is achieved. Within each sampling time, the NDMPC method can formulate and solve a constrained quadratic programming (QP) problem with time-varying desired formation pattern and get the optimal inputs for each robot in a distributed manner. The constraints of the system, as well as the switching structure brought by the changing topologies, can be tackled by utilizing the proposed method. In the end, numerical examples verify the effectiveness of the proposed formation control method.

Dynamic Data Integration for Resilience to Sensor Attacks in Multi-Agent Systems

In recent years the number of security incidents affecting control systems has increased. These incidents have shown the need to develop strategies to improve system resilience to cyber-attacks. This paper presents a practical implementation of a strategy to detect cyber-attacks and mitigate their effects on sensors of a multi-agent system. The proposed approach computes, in real-time, a convex combination of measurements from main and redundant sensors, producing a trust value of the measurement and feeding it to the controller. We implemented this approach on a testbed of ground robots in formation. Experimental results to various kinds of attacks and a key performance index show that the proposed strategy reduces the effects of attacks not only on the affected agent, but also prevents the propagation of the attack over the remaining agents.

A Comparison of Different Approaches for Formation Control of Nonholonomic Mobile Robots regarding Object Transport

Controlling the formation of several mobile robots allows for the connection of these robots to a large virtual unit. This enables a group of mobile robots to carry out tasks that a single robot could not perform. For this purpose, the use of nonholonomic mobile robots is especially useful, as they often have a higher payload and are suitable for a wider range of terrains. However, most research in the area of formation control is focused on holonomic robots, since their superior mobility allows for better control and allows for the research on more sophisticated control techniques. The remaining articles explicitly dealing with nonholonomic robots often do cover common controllers, but do not include realistic simulations or comparison of different controls on the same trajectory. Therefore, in this paper, we present a comparative analysis of two frequently used control approaches. We compare the behavior of a l-ψ-controller and a Cartesian reference-based controller with different types of reference value generation and pose determination. The evaluation of all resulting control schemes is based on the task of collaborative object transport. To do so, we selected performance criteria geared towards applicability in real processes. In addition, we used an error model, which takes into account the noise and accuracy of all sensors (IMU and encoder) as well as the drift in odometry caused by the slip of the robot’s wheels. The comparison includes a series of simulations using two trajectories with a changing number of robots and different formation geometries. In the simulations we got slightly better results for the Cartesian control law.

NPQ‐RRT ∗: An Improved RRT ∗ Approach to Hybrid Path Planning

In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ‐RRT ∗ with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.