Coordination Of Mobile Robots Research Articles

Motion Coordination of Multiple Autonomous Mobile Robots under Hard and Soft Constraints

This paper presents a distributed approach to the motion control problem for a platoon of unicycle robots moving through an unknown environment filled with static obstacles under multiple hard and soft operational constraints. Each robot has an onboard camera to determine its relative position in relation to its predecessor and proximity sensors to detect and avoid nearby obstascles. Moreover, no robot apart from the leader can independently localize itself within the given workspace. To overcome this limitation, we propose a novel distributed control protocol for each robot of the fleet, utilizing the Adaptive Performance Control (APC) methodology. By utilizing the APC approach to address input constraints via the on-line modification of the error specifications, we ensure that each follower effectively tracks its predecessor without encountering collisions with obstacles, while simultaneously maintaining visual contact with its preceding robot, thus ensuring the inter-robot visual connectivity. Finally, extensive simulation results are presented to demonstrate the effectiveness of the presented control system along with a real-time experiment conducted on an actual robotic system to validate the feasibility of the proposed approach in real-world scenarios.

Intelligent Planning for Large-Scale Multi-Robot Coordination

Robots will play a crucial role in the future and need to work as a team in increasingly more complex applications. Advances in robotics have laid the hardware foundations for building large-scale multi-robot systems. But how to coordinate robots intelligently is a difficult problem. We believe that graph-search-based planning can systematically exploit the combinatorial structure of multi-robot coordination problems and efficiently generate solutions with rigorous guarantees on correctness, completeness, and solution quality. We started with one problem that is central to many multi-robot applications. Multi-Agent Path Finding (MAPF) is an NP-hard problem of planning collision-free paths for a team of agents while minimizing their travel times. We addressed the MAPF problem from both (1) a theoretical perspective by developing efficient algorithms to solve large MAPF instances with completeness and optimality guarantees via a variety of AI and optimization technologies, such as constraint reasoning, heuristic search, stochastic local search, and machine learning, and (2) an applicational perspective by developing algorithmic techniques for integrating MAPF with task planning and execution for various multi-robot systems, such as mobile robot coordination, traffic management, drone swarm control, multi-arm assembly, and character control in video games. This paper is part of the AAAI-23 New Faculty Highlights.

Guiding Vector Fields for the Distributed Motion Coordination of Mobile Robots

In this article, we propose coordinating guiding vector fields to achieve two tasks simultaneously with a team of robots: first, the guidance and navigation of multiple robots to possibly different paths or surfaces typically embedded in 2-D or 3-D, and second, their motion coordination while tracking their prescribed paths or surfaces. The motion coordination is defined by desired parametric displacements between robots on the path or surface. Such a desired displacement is achieved by controlling the virtual coordinates, which correspond to the path or surface's parameters, between guiding vector fields. Rigorous mathematical guarantees underpinned by dynamical systems theory and Lyapunov theory are provided for the effective distributed motion coordination and navigation of robots on paths or surfaces from all initial positions. As an example for practical robotic applications, we derive a control algorithm from the proposed coordinating guiding vector fields for a Dubins-car-like model with actuation saturation. Our proposed algorithm is distributed and scalable to an arbitrary number of robots. Furthermore, extensive illustrative simulations and fixed-wing aircraft outdoor experiments validate the effectiveness and robustness of our algorithm.

Socially-inspired fully decentralized robot coordination

The necessity of the collision-free determination of movement trajectory can be observed among both animals and people. In a completely autonomous way, unrelated units make decisions on choosing their movement trajectory while moving in a common space. There is no explicit communication between the individual participants of the movement, and there is no central planner coordinating their activities. Nevertheless, large groups of unrelated movement participants are able to coordinate their actions, taking the trajectories of other road users into account and performing the task that is entrusted to them. These observations have inspired us to create a decentralized algorithm for coordinating the movement of mobile robots based on a model of the behavior of moving people. The need for the autonomous coordination of many objects and their management sets high requirements in terms of stability, scalability, and flexibility. The use of simple reactive controllers is a remedy that meets the limitations that are imposed on the algorithm. The solution provides methods for defining a collision-free path of movement based on the current observation of a robot’s environment. The behaviors that are modeled in the controller have been inspired by natural phenomena such as respect for those who stand higher in the social hierarchy, giving priority to people leaving a room, or generally known traffic rules. This paper presents algorithms for mobile robot coordination that are inspired by such phenomena. The algorithms were tested in both real and virtual environments in several settings, such as open space, a narrow passage, and a narrow corridor, and the results are presented. The experimental results were compared with the results of the recognized reciprocal velocity obstacles (RVO) (Van den Berg et al., 2008) method. Moreover, additional video materials are available online; these show the real-life robots in action when running the proposed route-planning algorithms.

Breaking Symmetries on Tessellation Graphs via Asynchronous Robots: The Line Formation Problem as a Case Study

Concerning the coordination of autonomous mobile robots, the main focus has been on the important class of Pattern Formation problems, where the robots are required to arrange themselves to form a given geometric shape. This class of problems has been extensively studied in the continuous environment (e.g., the Euclidean plane), whereas few results exist when robots move in a discretization of the plane, like infinite grids. In this environment, to form any pattern, the problem of breaking symmetries emerges. Breaking the symmetry by moving some leader robot is not a straightforward task due to the movement restrictions as all the adjacent nodes of the leader may be occupied. It may even happen that before obtaining the requested asymmetric configuration, most of the robots must be moved. Due to the asynchrony of robots, this fact greatly increases the difficulty of the problem. We assume very weak robots moving on any regular tessellation graph as a discretization of the Euclidean plane, and we devise an algorithm Abreak able to solve the Symmetry Breaking problem on both the square and triangular grids. It is important to note that Abreak is proposed so that it can be used as a module for solving more general problems. As a case study, we use Abreak to deal with the Line Formation problem, where n≥3 robots must arrange themselves to occupy n contiguous vertices along a grid line. In this respect, we first provide an algorithm ALF- able to partially solve this problem (it works with configurations in which it is not necessary to break symmetries), and then we show how Abreak and ALF- can be combined to form ALF. We provide a complete characterization of the solvability of the Line Formation problem on the considered topologies by showing that ALF solves the problem in each configuration where this is possible.

Coordination of nonholonomic mobile robots for diffusive threat defense

This paper studies coordination of a team of nonholonomic mobile robots with smart actuators for defending against invasive threat to a planar convex area. The threat refers to a kind of harmful substance such as chemical pollutant appearing outside and moving towards the area. The invasion of threat can be modeled by a 2D unsteady reaction-diffusion process. To reflect the adverse effect of threat on the area, a so-called risk intensity field is introduced. The value of risk intensity is equal to the concentration of threat measured by a static mesh sensor network. Based on this risk intensity field, a coordination control scenario using Voronoi tessellation is formulated. In order to minimize the actuator performance loss and reduce the total average risk intensity simultaneously, a generalized centroidal Voronoi tessellation (CVT) algorithm including optimal motion control and risk mitigation control is designed. The proposed algorithm is gradient-based and guides mobile robots to track their optimal trajectories asymptotically. Meanwhile, two conditions of choosing control gains are derived to keep the total average risk intensity below a safety level. Several simulation examples with different cases of threat invasion are provided and the advantage of proposed algorithm over traditional control method is presented.

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios.

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.

Robust finite-time containment control for high-order multi-agent systems with matched uncertainties under directed communication graphs

ABSTRACTIn this paper, we study the robust finite-time containment control problem for a class of high-order uncertain nonlinear multi-agent systems modelled as high-order integrator systems with bounded matched uncertainties. When relative state information between neighbouring agents is available, an observer-based distributed controller is proposed for each follower using the sliding mode control technique which solves the finite-time containment control problem under general directed communication graphs. When only relative output information is available, robust exact differentiators and high-order sliding-mode controllers are employed together with the distributed finite-time observers. It is shown that robust finite-time containment control can still be achieved in this situation. An application in the coordination of multiple non-holonomic mobile robots is used as an example to illustrate the effectiveness of the proposed control strategies.

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.

Zero-Sum Nonlinear Polynomial Game for Planar Robots Coordination

This paper proposes a scheme for the coordination of planar mobile robots based on Zero-Sum differential game model. The robots' dynamic are given in the polynomial approximation of the nonlinear model, we explore the so-called state-dependent Riccati equations to find a set of strategies that guarantee the effectively drive the robots to a particular formation. One of the robots acts as the leader following a free designed trayectory meanwhile the rest of the robots just follow him. The proposed solution is given as a polynomial Riccati-like state-dependent differential equation which utilizes a p-linear form tensor representation for its polynomial part. A numerical example is presented to illustrate effectiveness of the approach.

Effect of Wheel Slip in the Coordination of Wheeled Mobile Robots

Motion coordination of differential drive robots with wheel slip is considered in this work. In applications involving motion coordination of multiple wheeled vehicles, much of the existing work has assumed a pure rolling condition between the wheel and ground while deriving the vehicle dynamics and subsequently in the development of model-based controllers that can achieve and maintain the desired formation of vehicles. Wheel slip is common when using differential drive mobile robots as the orientation of the robot is achieved by commanding a velocity differential between the two driven wheels of the mobile robot. In formations of wheeled mobile robots, to maintain the desired spacing between vehicles, rapid accelerations and decelerations may be needed to maintain the desired spacing between vehicles. In this paper, we assume wheel slip and model the dynamics of each mobile robot with a simple Coulomb friction-based traction force model to distinguish between slip and no-slip conditions. Based on this dynamic model of the mobile robot with wheel slip, a formation controller is developed by limiting the torque to the wheel motors of each robot to avoid slip and achieve and maintain the desired formation. Experiments are conducted with a formation that is a platoon of three wheeled mobile robots. Experimental results are shown and discussed to investigate occurrence of wheel slip and its effect on coordination.

Decentralized Coordinated Tracking with Mixed Discrete–Continuous Decisions

In this paper, we study the problem of dynamically positioning a team of mobile robots for target tracking. We treat the coordination of mobile robots for target tracking as a joint team optimization to minimize uncertainty in target state estimates over a fixed horizon. The optimization is inherently a function of both the positioning of robots in continuous space and the assignment of robots to targets in discrete space. Thus, the robot team must make decisions over discrete and continuous variables. In contrast to methods that decouple target assignments and robot positioning, our approach avoids the strong assumption that a robot's utility for observing a target is independent of other robots’ observations. We formulate the optimization as a mixed integer nonlinear program and apply integer relaxation to develop an approximate solution in decentralized form. We demonstrate our coordinated multirobot tracking algorithm both in simulation and using a pair of mobile robotic sensor platforms to track moving pedestrians. Our results show that coupling target assignment and robot positioning realizes coordinated behaviors that are not possible with decoupled methods.

Robust formation control without velocity measurement of the leader robot

In this paper a control problem of leader–follower motion coordination of multiple nonholonomic mobile robots is addressed and subsequently in the proposed scheme, a reference trajectory generated based on the information from the leader is tracked by the follower robots. To alleviate demanded information on the leader, specifically to eliminate the measurement requirement or estimation of the leader's velocity and dynamics, a virtual vehicle is constructed whereby its trajectory converges to the reference trajectory of the follower. Trajectory tracking controller is then designed to allow the follower robot to track the virtual vehicle using neural network approximation, in combination with the backstepping and Lyapunov direct design technique and finally the performance and effectiveness of the controller is verified throughout the experiments.

Performance Optimisation of Mobile Robots for Search-and-Rescue

This paper presents a team performance optimisation system for multiple mobile robots in search-and-rescue operations, in which refugees are first discovered and subsequently robots are dispatched to transport themto shelters. Coordination of mobile robots involves two fundamental issues, namely task allocation and motion planning. While task allocation assigns jobs to robots, motion planning generates routes for robots to execute the assigned jobs. Task allocation and motion planning together play a pivotal role in optimisation of the robot team performance. These two issues become more challenging in dynamic search-and-rescue environments, where the refugees are unpredictably discovered at different locations and the traffic conditions of rescue zones keep changing. Weaddress these two issues by proposing an auction-based closed-loop module for task allocation and a bio-inspired intelligent module for motion planning. The task allocation module is characterised with a closed-loop bid adjustment mechanism to improve the bid accuracy even in light of stochastic rescue requests. The motion planning module is bio-inspired intelligent in that it features detection of imminent neighbours and responsiveness of virtual force navigation in dynamic traffic conditions. Simulations show that the proposed system is a practical tool to optimise the dynamic operations of search-and-rescue by a team of mobilerobots.

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

Mobile Robot Coordination and navigation with directional antennas in positionless Wireless Sensor Networks

Three schemes are proposed to coordinate and navigate mobile robots with directional antennas in a positionless wireless sensor network for the purpose of emergency rescue. The k-farthest-node forwarding scheme is for Waiting-for-Rescue (WFR) nodes to broadcast packets to ask mobile robots to come to help. The Mobile Robot Coordination (MRC) is to coordinate multiple mobile robots so that each WFR node is associated one nearby mobile node which is navigated by the Tree Assisted Navigation (TAN) scheme to fast reach the WFR node. The schemes' effectiveness is verified by the ns-2 simulator.

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.

Design of a Nonlinear Control Law for a Group of Differential-Wheel Robots Performing Rendezvous

The problems related to the coordination of mobile robots have been widely studied in the past and, because of the possible real scenarios, they are still considered one of the most interesting field of research. Even if many methods have been used to solve such problems, a new approach based on results borrowed from graph theory has been introduced in recent works. In particular, the coordination between agents relies on the possibility of solving the rendezvous problem and to drive all the agents to a predefined final state. Starting from these considerations, in this paper the stability of a group of differential-wheeled robots performing rendezvous by exploiting only local measurements is demonstrated and supported by means of simulations.

Feedback coordination of limited capability mobile robots

In some multi-robot applications, such as exploration, predefined task allocation and coordination can fail to function adequately. This failure is attributed to the inability to completely model a robot's interactions with the environment before task execution. Hence, the main focus of this paper is on a feedback coordination mechanism that executes periodically after initial task allocation. This feedback mechanism monitors the individual and group performance of worker robots. If the performance of a worker robot is unsatisfactory, a task reallocation algorithm adjusts the task-robot combinations of the team. Three cases of unsatisfactory robot performance that can be detected by the feedback mechanism include: complete failure, partial failure and poor performance. The task allocation and coordination strategy are applied to a multi-robot exploration task. Initial results from experiments in various types of environments indicate that the feedback coordination mechanism successfully identifies the thr...