Distributed Coordination Architecture for Cooperative Task Planning and Execution of Intelligent Multi-Robot Systems

2015 ◽  
pp. 407-426 ◽  
Author(s):  
Gen'ichi Yasuda
Keyword(s):  
Large Scale ◽  
Discrete Event ◽  
Robotic Systems ◽  
Task Planning ◽  
Distributed Coordination ◽  
Robot Systems ◽  
Concurrent Processes ◽  
Manufacturing Applications ◽  
Robot Cooperation ◽  
Multi Robot

This chapter provides a practical and intuitive way of cooperative task planning and execution for complex robotic systems using multiple robots in automated manufacturing applications. In large-scale complex robotic systems, because individual robots can autonomously execute their tasks, robotic activities are viewed as discrete event-driven asynchronous, concurrent processes. Further, since robotic activities are hierarchically defined, place/transition Petri nets can be properly used as specification tools on different levels of control abstraction. Net models representing inter-robot cooperation with synchronized interaction are presented to achieve distributed autonomous coordinated activities. An implementation of control software on hierarchical and distributed architecture is presented in an example multi-robot cell, where the higher level controller executes an activity-based global net model of task plan representing cooperative behaviors performed by the robots, and the parallel activities of the associated robots are synchronized without the coordinator through the transmission of requests and the reception of status.

Design and Implementation of Distributed Autonomous Coordinators for Cooperative Multi-Robot Systems

2020 ◽  
pp. 324-339
Author(s):  
Gen'ichi Yasuda
Keyword(s):  
Petri Nets ◽  
Discrete Event ◽  
Task Planning ◽  
Multiple Robots ◽  
Robot Systems ◽  
Consistent Manner ◽  
Concurrent Processes ◽  
Robot Cooperation ◽  
The Individual ◽  
Multi Robot

The paper presents a systematic method of the design of cooperative task planning and execution for complex robotic systems using multiple robots. Because individual robots can autonomously execute their dedicated tasks, in cooperative multi-robot systems, robotic activities should be designed as discrete event driven asynchronous, concurrent processes. Further, since robotic activities are hierarchically defined, control requirements should be specified in a proper and consistent manner on different levels of control abstraction. In this paper, Petri nets are adopted as a specification tool for task planning and execution by multiple robots. Based on place/transition Petri nets, control conditions for inter-robot cooperation with synchronized interaction are represented, and control rules to achieve distributed autonomous coordinated activities with synchronous and asynchronous communication are proposed. An implementation of net based control software on hierarchical and distributed architecture is presented for an example multi-robot cell, where the higher-level controller executes a global net model of task plan representing cooperative behaviors performed by the robots, and the parallel activities of the individual robots are synchronized through the transmission of requests and the reception of status between the associated lower-level local controllers.

Design and Implementation of Distributed Autonomous Coordinators for Cooperative Multi-Robot Systems

2016 ◽  
Vol 5 (4) ◽  
pp. 1-15 ◽  
Author(s):  
Gen'ichi Yasuda
Keyword(s):  
Petri Nets ◽  
Discrete Event ◽  
Task Planning ◽  
Multiple Robots ◽  
Control Rules ◽  
Robot Systems ◽  
Consistent Manner ◽  
Robot Cooperation ◽  
The Individual ◽  
Multi Robot

The paper presents a systematic method of the design of cooperative task planning and execution for complex robotic systems using multiple robots. Because individual robots can autonomously execute their dedicated tasks, in cooperative multi-robot systems, robotic activities should be designed as discrete event driven asynchronous, concurrent processes. Further, since robotic activities are hierarchically defined, control requirements should be specified in a proper and consistent manner on different levels of control abstraction. In this paper, Petri nets are adopted as a specification tool for task planning and execution by multiple robots. Based on place/transition Petri nets, control conditions for inter-robot cooperation with synchronized interaction are represented, and control rules to achieve distributed autonomous coordinated activities with synchronous and asynchronous communication are proposed. An implementation of net based control software on hierarchical and distributed architecture is presented for an example multi-robot cell, where the higher-level controller executes a global net model of task plan representing cooperative behaviors performed by the robots, and the parallel activities of the individual robots are synchronized through the transmission of requests and the reception of status between the associated lower-level local controllers.

Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios

2020 ◽  
Vol 39 (7) ◽  
pp. 856-892 ◽  
Author(s):  
Tingxiang Fan ◽  
Pinxin Long ◽  
Wenxi Liu ◽  
Jia Pan
Keyword(s):  
Reinforcement Learning ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Large Scale ◽  
Learning Algorithm ◽  
Free Action ◽  
Parameter Tuning ◽  
Movement Velocity ◽  
Robot Systems ◽  
Multi Robot

Developing a safe and efficient collision-avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generates its paths with limited observation of other robots’ states and intentions. Prior distributed multi-robot collision-avoidance systems often require frequent inter-robot communication or agent-level features to plan a local collision-free action, which is not robust and computationally prohibitive. In addition, the performance of these methods is not comparable with their centralized counterparts in practice. In this article, we present a decentralized sensor-level collision-avoidance policy for multi-robot systems, which shows promising results in practical applications. In particular, our policy directly maps raw sensor measurements to an agent’s steering commands in terms of the movement velocity. As a first step toward reducing the performance gap between decentralized and centralized methods, we present a multi-scenario multi-stage training framework to learn an optimal policy. The policy is trained over a large number of robots in rich, complex environments simultaneously using a policy-gradient-based reinforcement-learning algorithm. The learning algorithm is also integrated into a hybrid control framework to further improve the policy’s robustness and effectiveness. We validate the learned sensor-level collision-3avoidance policy in a variety of simulated and real-world scenarios with thorough performance evaluations for large-scale multi-robot systems. The generalization of the learned policy is verified in a set of unseen scenarios including the navigation of a group of heterogeneous robots and a large-scale scenario with 100 robots. Although the policy is trained using simulation data only, we have successfully deployed it on physical robots with shapes and dynamics characteristics that are different from the simulated agents, in order to demonstrate the controller’s robustness against the simulation-to-real modeling error. Finally, we show that the collision-avoidance policy learned from multi-robot navigation tasks provides an excellent solution for safe and effective autonomous navigation for a single robot working in a dense real human crowd. Our learned policy enables a robot to make effective progress in a crowd without getting stuck. More importantly, the policy has been successfully deployed on different types of physical robot platforms without tedious parameter tuning. Videos are available at https://sites.google.com/view/hybridmrca .

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.

scholarly journals Priority-Based Distributed Coordination for Heterogeneous Multi-Robot Systems With Realistic Assumptions

2021 ◽  
Vol 6 (3) ◽  
pp. 6131-6138
Author(s):  
Michele Cecchi ◽  
Matteo Paiano ◽  
Anna Mannucci ◽  
Alessandro Palleschi ◽  
Federico Pecora ◽  
...  
Keyword(s):  
Distributed Coordination ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Optimal Multi-robot Task Planning: from Synthesis to Execution (and Back)

2018 ◽  
Author(s):  
Francesco Leofante
Keyword(s):  
Optimal Solutions ◽  
Task Planning ◽  
Challenging Problem ◽  
Robot Systems ◽  
Ordering Constraints ◽  
On Line ◽  
Optimization Modulo Theories ◽  
Robot Task ◽  
And Robotics ◽  
Multi Robot

Integrated task planning and execution is a challenging problem with several applications in AI and robotics. In this work we consider the problem of generating and executing optimal plans for multi-robot systems under temporal and ordering constraints. More specifically, we propose an approach that unites the power of Optimization Modulo Theories with the flexibility of an on-line executive, providing optimal solutions for task planning, and runtime feedback on their execution.

scholarly journals Spatial winding: cooperative heterogeneous multi-robot system for fibrous structures

2020 ◽  
Vol 4 (3-4) ◽  
pp. 205-215
Author(s):  
Rebeca Duque Estrada ◽  
Fabian Kannenberg ◽  
Hans Jakob Wagner ◽  
Maria Yablonina ◽  
Achim Menges
Keyword(s):  
Large Scale ◽  
Fabrication Process ◽  
Physical Models ◽  
Frame Structures ◽  
Material System ◽  
Robotic Fabrication ◽  
New Material ◽  
Robot Cooperation ◽  
Digital Simulations ◽  
Multi Robot

AbstractThis research presents a cooperative heterogeneous multi-robot fabrication system for the spatial winding of filament materials. The system is based on the cooperation of a six-axis robotic arm and a customized 2 + 2 axis CNC gantry system. Heterogeneous multi-robot cooperation allows to deploy the strategy of Spatial Winding: a new method of sequential spatial fiber arrangement, based on directly interlocking filament-filament connections, achieved through wrapping one filament around another. This strategy allows to create lightweight non-regular fibrous space frame structures. The new material system was explored through physical models and digital simulations prior to deployment with the proposed robotic fabrication process. An adaptable frame setup was developed which allows the fabrication of a variety of geometries within the same frame. By introducing a multi-step curing process that integrates with the adaptable frame, the iterative production of continuous large-scale spatial frame structures is possible. This makes the structure’s scale agnostic of robotic reach and reduces the necessary formwork to the bare minimum. Through leveraging the capacities of two cooperating machines, the system allows to counteract some of their limitations. A flexible, dynamic and collaborative fabrication system is presented as a strategy to tailor the fiber in space and expand the design possibilities of lightweight fiber structures. The artifact of the proposed fabrication process is a direct expression of the material tectonics and the robotic fabrication system.

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