scholarly journals Petri Net Toolbox for Multi-Robot Planning under Uncertainty

2021 ◽  
Vol 11 (24) ◽  
pp. 12087
Author(s):  
Carlos Azevedo ◽  
António Matos ◽  
Pedro U. Lima ◽  
Jose Avendaño
Keyword(s):  
Heterogeneous Systems ◽  
Planning Under Uncertainty ◽  
Stress Tests ◽  
Action Execution ◽  
Robot System ◽  
Topological Map ◽  
Computational Performance ◽  
Robot Systems ◽  
Duration Uncertainty ◽  
Multi Robot

Currently, there is a lack of developer-friendly software tools to formally address multi-robot coordination problems and obtain robust, efficient, and predictable strategies. This paper introduces a software toolbox that encapsulates, in one single package, modeling, planning, and execution algorithms. It implements a state-of-the-art approach to representing multi-robot systems: generalized Petri nets with rewards (GSPNRs). GSPNRs enable capturing multiple robots, decision states, action execution states and respective outcomes, action duration uncertainty, and team-level objectives. We introduce a novel algorithm that simplifies the model design process as it generates a GSPNR from a topological map. We also introduce a novel execution algorithm that coordinates the multi-robot system according to a given policy. This is achieved without compromising the model compactness introduced by representing robots as indistinguishable tokens. We characterize the computational performance of the toolbox with a series of stress tests. These tests reveal a lightweight implementation that requires low CPU and memory usage. We showcase the toolbox functionalities by solving a multi-robot inspection application, where we extend GSPNRs to enable the representation of heterogeneous systems and system resources such as battery levels and counters.

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

A Novel Approach With Bayesian Networks to Multi-Robot Task Allocation in Dynamic Environments

2021 ◽  
Author(s):  
Ching-Wei Chuang ◽  
Harry H. Cheng
Keyword(s):  
Bayesian Networks ◽  
Task Allocation ◽  
Low Cost ◽  
Dynamic Environments ◽  
Modern World ◽  
Robot System ◽  
Novel Approach ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Abstract In the modern world, building an autonomous multi-robot system is essential to coordinate and control robots to help humans because using several low-cost robots becomes more robust and efficient than using one expensive, powerful robot to execute tasks to achieve the overall goal of a mission. One research area, multi-robot task allocation (MRTA), becomes substantial in a multi-robot system. Assigning suitable tasks to suitable robots is crucial in coordination, which may directly influence the result of a mission. In the past few decades, although numerous researchers have addressed various algorithms or approaches to solve MRTA problems in different multi-robot systems, it is still difficult to overcome certain challenges, such as dynamic environments, changeable task information, miscellaneous robot abilities, the dynamic condition of a robot, or uncertainties from sensors or actuators. In this paper, we propose a novel approach to handle MRTA problems with Bayesian Networks (BNs) under these challenging circumstances. Our experiments exhibit that the proposed approach may effectively solve real problems in a search-and-rescue mission in centralized, decentralized, and distributed multi-robot systems with real, low-cost robots in dynamic environments. In the future, we will demonstrate that our approach is trainable and can be utilized in a large-scale, complicated environment. Researchers might be able to apply our approach to other applications to explore its extensibility.

A Multi-Robot System Using Mobile Agents with Ant Colony Clustering

2010 ◽  
pp. 174-192
Author(s):  
Yasushi Kambayashi ◽  
Yasuhiro Tsujimura ◽  
Hidemi Yamachi ◽  
Munehiro Takimoto
Keyword(s):  
Communication Networks ◽  
Mobile Agents ◽  
Software Agents ◽  
Ant Colony ◽  
Multiple Robots ◽  
Robot System ◽  
Mobile Software ◽  
Robot Systems ◽  
Ant Colony Clustering ◽  
Multi Robot

This chapter presents a framework using novel methods for controlling mobile multiple robots directed by mobile agents on a communication networks. Instead of physical movement of multiple robots, mobile software agents migrate from one robot to another so that the robots more efficiently complete their task. In some applications, it is desirable that multiple robots draw themselves together automatically. In order to avoid excessive energy consumption, we employ mobile software agents to locate robots scattered in a field, and cause them to autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO) method. ACO is the swarm-intelligence-based method that exploits artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. Even though there is much room to improve the collaboration of multiple agents and ACO, the current results suggest a promising direction for the design of control mechanisms for multi-robot systems. In this chapter, we focus on the implementation of the controlling mechanism of the multi-robot system using mobile agents.

Dynamic model based formation control and obstacle avoidance of multi-robot systems

Robotica ◽  
2008 ◽  
Vol 26 (3) ◽  
pp. 345-356 ◽  
Author(s):  
Celso De La Cruz ◽  
Ricardo Carelli
Keyword(s):  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Formation Control ◽  
Inverse Dynamics ◽  
Single Equation ◽  
Model Parameters ◽  
Robot System ◽  
System A ◽  
Robot Systems ◽  
Multi Robot

SUMMARYThis work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

scholarly journals Exploring Effects of Information Filtering With a VR Interface for Multi-Robot Supervision

2021 ◽  
Vol 8 ◽  
Author(s):  
Daniel Butters ◽  
Emil T. Jonasson ◽  
Vijay M. Pawar
Keyword(s):  
Interface Design ◽  
User Study ◽  
Internal State ◽  
Information Filtering ◽  
3D Interaction ◽  
Robot System ◽  
Remote Maintenance ◽  
Robot Systems ◽  
Initial Work ◽  
Multi Robot

Supervising and controlling remote robot systems currently requires many specialised operators to have knowledge of the internal state of the system in addition to the environment. For applications such as remote maintenance of future nuclear fusion reactors, the number of robots (and hence supervisors) required to maintain or decommission a facility is too large to be financially feasible. To address this issue, this work explores the idea of intelligently filtering information so that a single user can supervise multiple robots safely. We gathered feedback from participants using five methods for teleoperating a semi-autonomous multi-robot system via Virtual Reality (VR). We present a novel 3D interaction method to filter the displayed information to allow the user to read information from the environment without being overwhelmed. The novelty of the interface design is the link between Semantic and Spatial filtering and the hierarchical information contained within the multi robot system. We conducted a user study including a cohort of expert robot teleoperators comparing these methods; highlighting the significant effects of 3D interface design on the performance and perceived workload of a user teleoperating many robot agents in complex environments. The results from this experiment and subjective user feedback will inform future investigations that build upon this initial work.

scholarly journals Consensus Algorithms Based Multi-Robot Formation Control under Noise and Time Delay Conditions

2019 ◽  
Vol 9 (5) ◽  
pp. 1004 ◽  
Author(s):  
Heng Wei ◽  
Qiang Lv ◽  
Nanxun Duo ◽  
GuoSheng Wang ◽  
Bing Liang
Keyword(s):  
Time Delay ◽  
Mobile Robot ◽  
Formation Control ◽  
Second Order ◽  
Multiple Time ◽  
Consensus Problem ◽  
Robot System ◽  
Maximum Time ◽  
Robot Systems ◽  
Multi Robot

In recent years, the formation control of multi-mobile robots has been widely investigated by researchers. With increasing numbers of robots in the formation, distributed formation control has become the development trend of multi-mobile robot formation control, and the consensus problem is the most basic problem in the distributed multi-mobile robot control algorithm. Therefore, it is very important to analyze the consensus of multi-mobile robot systems. There are already mature and sophisticated strategies solving the consensus problem in ideal environments. However, in practical applications, uncertain factors like communication noise, communication delay and measurement errors will still lead to many problems in multi-robot formation control. In this paper, the consensus problem of second-order multi-robot systems with multiple time delays and noises is analyzed. The characteristic equation of the system is transformed into a quadratic polynomial of pure imaginary eigenvalues using the frequency domain analysis method, and then the critical stability state of the maximum time delay under noisy conditions is obtained. When all robot delays are less than the maximum time delay, the system can be stabilized and achieve consensus. Compared with the traditional Lyapunov method, this algorithm has lower conservativeness, and it is easier to extend the results to higher-order multi-robot systems. Finally, the results are verified by numerical simulation using MATLAB/Simulink. At the same time, a multi-mobile robot platform is built, and the proposed algorithm is applied to an actual multi-robot system. The experimental results show that the proposed algorithm is finally able to achieve the consensus of the second-order multi-robot system under delay and noise interference.

Overview of Search and Rescue from Robotics to Wireless Sensors and Robots Networks

2016 ◽  
Vol 4 (2) ◽  
pp. 16-33 ◽  
Author(s):  
Sarah Allali ◽  
Mahfoud Benchaïba
Keyword(s):  
Wireless Sensors ◽  
Search And Rescue ◽  
Robotic Systems ◽  
Multiple Robots ◽  
Robot System ◽  
Research Challenges ◽  
Open Research ◽  
Robot Systems ◽  
Rescue System ◽  
Multi Robot

In the recent years, many researchers have shown interest in developing search and rescue system composed of one or multiple robots, which have the mission of finding victims and identifying the potential hazards. To enhance the robotic systems there is a growing trend of integrating wireless sensor networks (WSNs) to robots and multi-robot systems, which gives more awareness of the environments. In the first part of this article, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain challenges related to these systems and tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the system that integrates WSNs with robots and the advantages that brings this latter. In addition, they cite tasks and missions that are achieved in a better way with a cooperation of WSN and robots. Furthermore, the authors expose and discuss the remarkable research, challenges and the open research challenges that includes this cooperation.

Overview of Search and Rescue From Robotics to Wireless Sensors and Robots Networks

2019 ◽  
pp. 1212-1231
Author(s):  
Sarah Allali ◽  
Mahfoud Benchaïba
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensors ◽  
Search And Rescue ◽  
Wireless Sensor ◽  
Multiple Robots ◽  
Robot System ◽  
Research Challenges ◽  
Robot Systems ◽  
Rescue System ◽  
Multi Robot

In the recent years, many researchers have shown interest in developing search and rescue system composed of one or multiple robots, which have the mission of finding victims and identifying the potential hazards. To enhance the robotic systems there is a growing trend of integrating wireless sensor networks (WSNs) to robots and multi-robot systems, which gives more awareness of the environments. In the first part of this article, the authors present a review of robotic system and their environments in search and rescue systems. Additionally, they explain challenges related to these systems and tasks that a robot or a multi-robot system should execute to fulfil the search and rescue activities. As a second part, the authors expose the system that integrates WSNs with robots and the advantages that brings this latter. In addition, they cite tasks and missions that are achieved in a better way with a cooperation of WSN and robots. Furthermore, the authors expose and discuss the remarkable research, challenges and the open research challenges that includes this cooperation.

Fuzzy coordination through measure information sharing of multi-robot system: A case study

2021 ◽  
pp. 1-8
Author(s):  
Xuefeng Dai ◽  
Jiazhi Wang ◽  
Dahui Li ◽  
Yanchun Wang
Keyword(s):  
Robot System ◽  
Fuzzy Membership Functions ◽  
System A ◽  
Parameter Update Law ◽  
Robot Systems ◽  
Potential Applications ◽  
The Individual ◽  
Logic Reasoning ◽  
Multi Robot

Multi-robot systems have many potential applications; however, the available results for coordination were based on qualitative information. Fuzzy logic reasoning has a feature of human being thinking, so a novel coordinated algorithm is proposed. The algorithm utilizes sharing sensing information of rooms and semantic robots to coordinating robots in a structured environment exploration. The approach divides all teammate robots into two classes according to robot exploration performance, and divides rooms into large, medium and small ones according to estimations of the individual areas. On the purpose of minimizing exploration time of the system, the reasoning coordination assigns large room to good performance robot, and vice versa. A parameter update law is introduced for fuzzy membership functions. Finally, the results are validated by computer simulations for a structured environment.

scholarly journals Hunting strategy for multi-robot based on wolf swarm algorithm and artificial potential field

2022 ◽  
Vol 25 (1) ◽  
pp. 159
Author(s):  
Oussama Hamed ◽  
Mohamed Hamlich ◽  
Mohamed Ennaji
Keyword(s):  
Potential Field ◽  
Artificial Potential Field ◽  
Moving Target ◽  
Robot System ◽  
Cooperative Hunting ◽  
Robot Systems ◽  
Dynamic Target ◽  
Swarm Algorithm ◽  
Hunting Strategy ◽  
Multi Robot

The cooperation and coordination in multi-robot systems is a popular topic in the field of robotics and artificial intelligence, thanks to its important role in solving problems that are better solved by several robots compared to a single robot. Cooperative hunting is one of the important problems that exist in many areas such as military and industry, requiring cooperation between robots in order to accomplish the hunting process effectively. This paper proposed a cooperative hunting strategy for a multi-robot system based on wolf swarm algorithm (WSA) and artificial potential field (APF) in order to hunt by several robots a dynamic target whose behavior is unexpected. The formation of the robots within the multi-robot system contains three types of roles: the leader, the follower, and the antagonist. Each role is characterized by a different cognitive behavior. The robots arrive at the hunting point accurately and rapidly while avoiding static and dynamic obstacles through the artificial potential field algorithm to hunt the moving target. Simulation results are given in this paper to demonstrate the validity and the effectiveness of the proposed strategy.

Sign in / Sign up

Export Citation Format

Share Document