Deadlock Avoidance Research Articles

Multiple Mobile Robots Coordination in Shared Workspace for Task Makespan Minimization

In this paper we consider a system of multiple mobile robots (MMRS) and the process of their concurrent motion in a shared two-dimensional workspace. The goal is to plan the robot movement along given fixed paths so as to minimize the completion time of all the robots while ensuring that they never collide. Thus, the considered problem combines the problems of robot schedule optimization with collision and deadlock avoidance. The problem formulation is presented and its equivalent reformulation that does not depend explicitly on the geometry of the robot paths is proposed. An event-based solution representation is proposed, allowing for a discrete optimization approach. Two types of possible deadlocks are identified and deadlock avoidance procedures are discussed. We proposed two types of solving methods. First, we implemented two metaheuristics: the local-search-based taboo search as well as the population-based artificial bee colony. Next, we implemented 14 simple constructive algorithms, employing dispatch rules such as first-in first-out, shortest distance remaining first, and longest distance remaining first, among others. A set of problem instances for different numbers of robots is created and provided as a benchmark. The effectiveness of the solving methods is then evaluated by simulation using the generated instances. Both deterministic and lognormal-distributed uncertain robot travel times are considered. The results prove that the taboo search metaheuristic obtained the best results for both deterministic and uncertain cases, with only artificial bee colony and a few constructive algorithms managing to remain competitive. Detailed results as well as ideas to further improve proposed methods are discussed.

Relation between leader–follower consensus control and feedback vertex sets

ABSTRACT Leader–follower consensus control is a kind of consensus control, where some special agents, called the leaders, have relatively high flexibility in changing their states, and the other agents, called the followers, follow the leaders. One of the important issues for leader–follower consensus control is a leader selection problem, i.e. determining leaders to achieve a desired performance. On the other hand, the notion of a feedback vertex set is well-known in graph theory. Feedback vertex sets are known to play an important role in various problems, e.g. deadlock avoidance and sensing node selection of biological networks. Thus, they are expected to be closely related to leader–follower consensus control. However, their relationship has never been studied so far. This paper discloses the relationship between leader selection and feedback vertex sets. We deal with a problem of finding a minimum leader set to achieve the fastest convergence to consensus and show that a solution to the leader selection problem is given by a feedback vertex set.

A Place-Timed Petri Net-Based Method to Avoid Deadlock and Conflict in Railway Networks

The real-time traffic control of railway networks imposes safety constraints and authorizes movements of trains. This work deals with it by focusing on conflict and deadlock avoidance problems. A place-timed Petri net model is developed for a railway network. Based on it, a conflict avoidance method is presented to ensure that safety principles in railway networks are respected. Also, a polynomial deadlock avoidance policy based on the Banker’s algorithm is proposed. It authorizes the movement of trains between block sections and stations. The proposed conflict avoidance method and deadlock avoidance policy together ensure a railway network to be conflict-free and deadlock-free. Experimental results show that they are effective and efficient.

Collision and Deadlock Avoidance in Multi-Robot Systems Based on Glued Nodes

Dear editor, In this letter, we would like to discuss a method to avoid collisions and deadlocks in multi-robot systems based on a new concept of glued nodes.

Arc Model and DDG: Deadlock Avoidance and Detection in Torus NoC

Wraparound channels in Torus Network-on-Chip (NoC) help in reducing overall hop counts traversed by traffic. However, the cyclic paths created by wraparound channel make Torus NoC deadlock prone. Turn model and Channel Dependency Graph (CDG) are two classical approaches used for detecting and avoiding deadlock in NoC. In this work, we propose an Arc model for avoiding deadlock in Torus NoC. Arc model is an extension to Turn model and is useful for deadlock avoidance in Torus. Directional Dependency Graph (DDG) is also presented in this work by combining both Turn model and CDG for detecting deadlock in Torus NoC. DDG is a simpler approach for identifying deadlock scenarios, formulating deadlock avoidance and showing deadlock freedom while using Arc model along with a set of Turns.

GTO-MPC-Based Target Chasing Using a Quadrotor in Cluttered Environments

This article addresses the challenging problem of chasing an escaping target using a quadrotor in cluttered environments. To tackle these challenges, we propose a guided time-optimal model predictive control (GTO-MPC)-based practical framework to generate chasing trajectories for the quadrotor. A jerk limited approach is first adopted to find a time-optimal jerk limited trajectory (JLT), an initial reference for the quadrotor to track, without taking into account surrounding obstacles and potential threats. An MPC-based replanning framework is then applied to approximate the JLT together with the consideration of other issues such as flight safety, line-of-sight maintenance, and deadlock avoidance. Combined with a neural network, the proposed GTO-MPC framework can efficiently generate chasing trajectories that guarantee flight smoothness and kinodynamic feasibility. Our simulation and actual experimental results show that the proposed technique is highly effective.

Dynamic Collision and Deadlock Avoidance for Multiple Robotic Manipulators

A flexible operation of multiple robotic manipulators operating in a dynamic environment requires online trajectory planning to ensure collision-free trajectories. In this work, we propose a real-time capable motion control algorithm, based on nonlinear model predictive control, which accounts for static and dynamic obstacles. The proposed algorithm is realized in a distributed scheme, where each robot optimizes its own trajectory with respect to the related objective and constraints. We propose a novel approach for collision avoidance between multiple robotic manipulators, where each robot accounts for the predicted movement of the neighboring robots. Additionally, we propose a method to reliably detect and resolve deadlocks occurring in a setup of multiple robotic manipulators. We validate our approach on pick and place scenarios involving multiple robotic manipulators operating in a common workspace in a realistic simulation environment set up in Gazebo. The robots are controlled using the Robot Operating System. Our approach scales up to 4 manipulators and computes a path for each robot in a simultaneous pick and place operation in 94% of all investigated cases without deadlock detection and 100 % of cases with the proposed deadlock resolution algorithm. In contrast, the investigated conventional path planners, such as PRM, PRM*, CHOMP and RRT-Connect, successfully plan a trajectory in at most 54% of all investigated cases for a simultaneous operation of 4 robotic manipulators hindering their application in setups of multiple manipulators.

Maximal Linear Deadlock Avoidance Policies for Sequential Resource Allocation Systems: Characterization, Computation, and Approximation

The problem of maximally permissive deadlock avoidance for sequential resource allocation systems (RAS) is a well-defined problem in the current controls literature. The corresponding supervisor is known as the maximally permissive deadlock avoidance policy (DAP), and it can be perceived as a classifier effecting the dichotomy of the underlying state space into its “safe” and “unsafe” subspaces. In the deployment of the maximally permissive DAP, an important issue is the selection of an effective and computationally efficient representation of the aforementioned dichotomy. A popular such representation is the “linear classifier,” where the admissibility of any given RAS state is resolved based on its ability to satisfy a given set of linear inequalities. However, linear classifiers cannot provide effective representation of the maximally permissive DAP for all RAS instantiations. Hence, this article provides a methodology for synthesizing linear DAPs for any given RAS instance that might not be maximally permissive in the original sense of this term, but observe a more relaxed notion of “maximality” that is defined within the particular space of the DAPs that admit a linear representation. The presented developments formally define this new DAP class, and provide the necessary algorithms for the synthesis or the systematic approximation of maximal linear DAPs for any given RAS instance.

Hybrid particle swarm optimization algorithm for scheduling flexible assembly systems with blocking and deadlock constraints

This paper focuses on the scheduling problem of flexible assembly systems (FASs) without intermediate buffers. The main characteristic of the problem is that as no intermediate buffer exists between consecutive machines, blocking and deadlock constraints must be considered. Petri nets are used to model the considered FASs, and a novel hybrid particle swarm optimization (HPSO) algorithm is proposed to minimize the makespan. The proposed algorithm is the combination of the discrete PSO, particle repairing algorithm, particle improvement strategy, and local search method. First, each candidate solution for the problem is encoded as a permutation with repetition of part numbers, and can be uniquely decoded into a sequence of transitions. To ensure the feasibility of solutions, a repairing algorithm is developed, in which a deadlock avoidance policy is used. Then, a particle improvement policy is proposed to improve the performance of particles. Meanwhile, a local search method is designed and incorporated into HPSO to improve its search ability. Experiments are conducted to verify the effectiveness of the particle improvement policy and local search method. Comparisons between HPSO and ten other algorithms are performed. The comparison results and analysis show that our proposed algorithm can find feasible solutions for all tested instances, and is superior to other scheduling algorithms in terms of finding better solutions and performance stability.

Robotic industrial automation simulation-optimization for resolving conflict and deadlock

PurposeThe purpose of this study is to investigate the benefits of the turning point layout; a simulation model being applicable for strategic level is designed that compares systems with and without turning points. Specifically, the avoidance of deadlocks and prevention of conflicts is substantial.Design/methodology/approachOptimization process for different layouts and configuration of autonomous guided vehicles (AGVs) are worked out using statistical methods for design parameters. Regression analysis is used to find effective design parameters and analysis of variance is applied for adjusting critical factors. Also, the optimal design is then implemented in a manufacturing system for an industrial automation and the results are reported.FindingsThe outputs imply the effectiveness of the proposed approach for real industrial cases. This research will combine both simulation-based method and optimization technique to improve the quality of solutions.Originality/valueIn AGV systems, the begin-end combinations are usually connected by using a fixed layout, which is not the optimal path. The capability of these configurations is limited and often the conflict of multiple AGVs and deadlock are inevitable. By appearing more flexible layouts and advanced technology, the positioning and dispatching of AGVs increased. A new concept would be to determine each path dynamically. This would use the free paths for AGVs leading to overcome the conflicts and deadlocks.

Decentralized MPC-Based Trajectory Generation for Multiple Quadrotors in Cluttered Environments

Challenges in motion planning for multiple quadrotors in complex environments lie in overall flight efficiency and the avoidance of obstacles, deadlock, and collisions among themselves. In this paper, we present a gradient-free trajectory generation method for multiple quadrotors in dynamic obstacle-dense environments with the consideration of time consumption. A model predictive control (MPC)-based approach for each quadrotor is proposed to achieve distributed and asynchronous cooperative motion planning. First, the motion primitives of each quadrotor are formulated as the boundary state constrained primitives (BSCPs) which are constructed with jerk limited trajectory (JLT) generation method, a boundary value problem (BVP) solver, to obtain time-optimal trajectories. They are then approximated with a neural network (NN), pre-trained using this solver to reduce the computational burden. The NN is used for fast evaluation with the guidance of a navigation function during optimization to guarantee flight safety without deadlock. Finally, the reference trajectories are generated using the same BVP solver. Our simulation and experimental results demonstrate the superior performance of the proposed method.

A* Based Routing and Scheduling Modules for Multiple AGVs in an Industrial Scenario

A multi-AGV based logistic system is typically associated with two fundamental problems, critical for its overall performance: the AGV’s route planning for collision and deadlock avoidance; and the task scheduling to determine which vehicle should transport which load. Several heuristic functions can be used according to the application. This paper proposes a time-based algorithm to dynamically control a fleet of Autonomous Guided Vehicles (AGVs) in an automatic warehouse scenario. Our approach includes a routing algorithm based on the A* heuristic search (TEA*—Time Enhanced A*) to generate free-collisions paths and a scheduling module to improve the results of the routing algorithm. These modules work cooperatively to provide an efficient task execution time considering as basis the routing algorithm information. Simulation experiments are presented using a typical industrial layout for 10 and 20 AGVs. Moreover, a comparison with an alternative approach from the state-of-the-art is also presented.

Algorithm and model for improve the avoiding of deadlock with increasing efficiency of resource allocation in cloud environment

Recently, cloud computing has been the most popular method among all other promising technologies that provides the service for many users at the same time. all users can reach and use the resource that is provided by the Virtual Machines (VMs). Hence users process, data must arrive to the resources to perform as a disturbed system, which provides dynamical scale services and virtualized resources. As a result of limitation of resources, the deadlock status may occur in such type of systems. In this paper, we have designed an algorithm that could increase the efficiency of deadlock avoidance. Our technique will use the attribute of execution time in the process to get better resource allocation in additional to the checking system to stay in safe state and free of deadlock.

Modelling and Control of Resource Allocation Systems within Discrete Event Systems by Means of Petri Nets -- Part 1: Invariants, Siphons and Traps in Deadlock Avoidance

Solving the deadlocks avoidance problem in Resource Allocation Systems (RAS) in Discrete-Event Systems (DES) is a rife problem, especially in Flexible Manufacturing Systems (FMS), alias Automated Manufacturing Systems (AMS). Petri Nets (PN) are an effectual tool often used at this procedure. In principle, there are two basic approaches how to deal with deadlocks in RAS based on PN. They are listed and illustrated here. First of the approaches is realized by means of the supervisor based on P-invariants of PN, while the second one is realized by means of the supervisor based on PN siphons. While the first approach needs to know the reachability graph/tree (RG/RT) expressing the causality of the development of the PN model of RAS, in order to find (after its thorough analysis) the deadlocks, the second approach needs the thorough analysis of the PN model structure by means of finding siphons and traps. Next, both approaches will be applied on the same PN model of RAS and the effectiveness of the achievement of their results will be compared and evaluated. Several simple illustrative examples will be introduced. For the in-depth analysis of the problem of deadlock avoiding, next Part 2 of this paper is prepared, where the newest research will be introduced and illustrated on more complicated examples. If necessary (because of the limited length of particular papers), also the third part – Part 3, will be prepared.

Symbolic Refinement of Extended State Machines with Applications to the Automatic Derivation of Sub-Components and Controllers

Nowadays, extended state machines are prominent requirements specification techniques due to their capabilities of modeling complex systems in a compact way. These machines extend the standard state machines with variables and have transitions guarded by enabling predicates and may include variable update statements. Given a system modeled as an extended state machine, with possibly infinite state space and some non-controllable (parameterized) interactions, a pruning procedure is proposed to symbolically derive a maximal sub-machine of the original system that satisfies certain conditions; namely, some safeness and absence of undesirable deadlocks which could be produced during pruning. In addition, the user may specify, as predicates associated with states, some general goal assertions that should be preserved in the obtained sub-machine. Further, one may also specify some specific requirements such as the elimination of certain undesirable deadlocks at states, or fail states that should never be reached. Application examples are given considering deadlock avoidance and loops including infinite loops over non-controllable interactions showing that the procedure may not terminate. In addition, the procedure is applied for finding a controller of a system to be controlled. The approach generalizes existing work in respect to the considered extended machine model and the possibility of user defined control objectives written as assertions at states.

Deadlock Avoidance Algorithms for Recursion-Tree Modeled Requests in Parallel Executions

We present an extension of the bankers algorithm to resolve deadlock for programs whose resource-request graph can be modeled as a recursion tree for parallel execution. Our algorithm implements the bankers logic, with the key difference being that some properties of the tree are fully exploited to improve the resource utilization and safety check in deadlock avoidance. For an n-node tree modeled program making requests to m types of resources, our recursion-tree based algorithm can obtain a time complexity of O(mn loglogn) on average in safety check while reducing the conservativeness in resource utilization. We reap these benefits by proposing a concept of the resource critical tree and leverage it to localize the maximum claim associated with each node in the tree. To tackle the case when the tree model is not statically known, we relax the definition of a local maximum claim by sacrificing some resource utilization. With this trade-off, the algorithm can resolve the deadlock and achieve more efficient safety checks within time of O(m loglogn). Our empirical studies on a two-dimensional integration problem on sparse grids show that the proposed algorithms can reduce resource utilization conservativeness and improve avoidance performance by minimizing the number of safety checks.

Event Circular Waits and Their Analysis via Petri Nets

Deadlock control of automated manufacturing systems has been widely investigated in recent decades. According to classical Coffman theory, resource circular wait (RW) is viewed as a necessary condition for deadlocks to occur. However, the fact is not as simple as so. Counterexamples are presented to show that RWs do not necessarily appear together with deadlocks. Event circular waits (EWs) are proposed as an alternative to represent a fundamental necessary condition of deadlocks. First, we present the formal definitions of EWs in a type of Petri nets, i.e., weighted augmented marked graphs (WAMGs), and show that EWs are more general and essential than RWs in describing the cause of deadlocks. Second, we show a new classification of siphons, i.e., types I, II, III, and IV, and illustrate the relationship between undermarked siphons and EWs in the WAMGs. Third, we show that EWs are more efficient than RWs for deadlock avoidance since deadlocks can be avoided earlier at a specified marking by using EWs rather than RWs. Several examples are given to clarify the theory throughout this paper.

An agent-based Flexible Manufacturing System controller with Petri-net enabled algebraic deadlock avoidance

This work focuses on the efficient design of a controller for a Flexible Manufacturing System (FMS) using Agents. The necessary agents were selected and defined according to the Design of Agent-based Production Control Systems (DACS) methodology. The Contract Net Protocol (CNP) was applied for agent communication and interaction. A particular Algebraic Deadlock Avoidance Policy (DAP) is efficiently embedded into CNP. As a result the multi agent system is live and deadlock–free. Feasibility analysis of the controller was performed by exploiting Resource Allocation Systems techniques being defined in the framework of Petri Net theory. The controller is demonstrated in simulation mode in the framework of the Java Agent Development Framework (JADE) system

Remote Control: A Simple Deadlock Avoidance Scheme for Modular Systems-on-Chip

Ever increasing performance demand and shrinking in the transistor size together result in complex and dense packing in large chips. That motivates designers to opt for many small specialized hardware modules in a chip to extract maximum performance benefits with relatively lower complexity and cost. These altogether opens up new directions for heterogeneous modular System-on-Chip (SoC) research, where a large system is built by assembling small independently designed chiplets (small chips). We focus on the communication aspect of such SoCs, especially the newly observed deadlock among chiplets. Even though deadlock is a classic problem in networks and many solutions are available, the modular SoC design demands customized solutions that preserves the design flexibility for chiplet designers. We propose <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Remote Control (RC)</i> , a simple routing oblivious deadlock avoidance scheme based on selective injection-control mechanism. Along with guarantee on deadlock freedom, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RC</i> aims to provide a methodology to make each independently designed chiplet seamlessly integrate in any modular SoCs. We achieve up to 56.34% throughput and 15.49% zero load latency improvements on synthetic traffic and up to 20% speedup on real workloads taken from vast range of benchmark suites, over the state-of-the-art turn restriction based technique applied in the modular SoC domain.

A Robust Control Approach to Automated Manufacturing Systems Allowing Multitype and Multiquantity of Resources With Petri Nets

Up to now, the supervision and control of deadlock-free resource allocation has received considerable attention, particularly regarding their deadlock problems. To date, most solutions have supposed that allocated resources never fail. However, this is quite the opposite in reality since some resources may fail unexpectedly. A robust system should be resilient to such failures. In this paper, resources are divided into reliable ones and unreliable ones. On the basis of the deadlock avoidance algorithm which is proposed for the problem of deadlocks, we propose a robust control algorithm in the paradigm of systems of sequential systems with shared resources, which can acquire and release resources in a multitype and multiquantity way. It is validated to be a polynomially complex robust control algorithm by the distributivity analysis. Finally, experimental results show that the proposed approaches are effective as well as efficient in response to resource failures.