针对多机器人协作中存在的并发性较少、协商通信的实时性与高效性较差以及问题学习空间维数灾难等问题,提出一种基于π-MaxQ学习的多机器人主体协作方法。定义了机器人的公共知识、信念、目标、意图、承诺、信任、知识更新等心智状态,...针对多机器人协作中存在的并发性较少、协商通信的实时性与高效性较差以及问题学习空间维数灾难等问题,提出一种基于π-MaxQ学习的多机器人主体协作方法。定义了机器人的公共知识、信念、目标、意图、承诺、信任、知识更新等心智状态,扩充了基于心智状态的KQML(Knowledge Query and Manipulation Language)通信原语,并基于MaxQ方法构建了联合奖励函数。实验证明了方法的有效性。展开更多
This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behav...This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behavior rules to help to plan out welding paths for robots collision free, which is a base fixed problem. Finally, we testify the algorithm to be practical in virtual environment, and output robot programs to direct production process. This new way will help us to find a new development method for multiple robots path planning.展开更多
Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievem...Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievements in agricultural robotics,specifically those that are used for autonomous weed control,field scouting,and harvesting.Object identification,task planning algorithms,digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming.The concepts of multi-robots,human-robot collaboration,and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming.It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information.For the case of robotic harvesting,an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators.While robots are becoming the inseparable parts of the modern farms,our conclusion is that it is not realistic to expect an entirely automated farming system in the future.展开更多
Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplina...Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments.With the exception of milking robots,the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date.To accelerate this pace,simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios.This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications.The key features and performance efficiency of three selected simulators were also compared.A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform.Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard.It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment.This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces,algorithms,and reusing the materials.展开更多
文摘针对多机器人协作中存在的并发性较少、协商通信的实时性与高效性较差以及问题学习空间维数灾难等问题,提出一种基于π-MaxQ学习的多机器人主体协作方法。定义了机器人的公共知识、信念、目标、意图、承诺、信任、知识更新等心智状态,扩充了基于心智状态的KQML(Knowledge Query and Manipulation Language)通信原语,并基于MaxQ方法构建了联合奖励函数。实验证明了方法的有效性。
基金Natural Science Foundation of China (No.5 98895 0 5 )
文摘This paper described a new method to plan out welding paths for multiple robots in virtual manufacturing environment. We first distribute welding tasks and priority for multi robots, and then apply corresponding behavior rules to help to plan out welding paths for robots collision free, which is a base fixed problem. Finally, we testify the algorithm to be practical in virtual environment, and output robot programs to direct production process. This new way will help us to find a new development method for multiple robots path planning.
文摘Digital farming is the practice of modern technologies such as sensors,robotics,and data analysis for shifting from tedious operations to continuously automated processes.This paper reviews some of the latest achievements in agricultural robotics,specifically those that are used for autonomous weed control,field scouting,and harvesting.Object identification,task planning algorithms,digitalization and optimization of sensors are highlighted as some of the facing challenges in the context of digital farming.The concepts of multi-robots,human-robot collaboration,and environment reconstruction from aerial images and ground-based sensors for the creation of virtual farms were highlighted as some of the gateways of digital farming.It was shown that one of the trends and research focuses in agricultural field robotics is towards building a swarm of small scale robots and drones that collaborate together to optimize farming inputs and reveal denied or concealed information.For the case of robotic harvesting,an autonomous framework with several simple axis manipulators can be faster and more efficient than the currently adapted professional expensive manipulators.While robots are becoming the inseparable parts of the modern farms,our conclusion is that it is not realistic to expect an entirely automated farming system in the future.
文摘Research efforts for development of agricultural robots that can effectively perform tedious field tasks have grown significantly in the past decade.Agricultural robots are complex systems that require interdisciplinary collaborations between different research groups for effective task delivery in unstructured crops and plants environments.With the exception of milking robots,the extensive research works that have been carried out in the past two decades for adaptation of robotics in agriculture have not yielded a commercial product to date.To accelerate this pace,simulation approach and evaluation methods in virtual environments can provide an affordable and reliable framework for experimenting with different sensing and acting mechanisms in order to verify the performance functionality of the robot in dynamic scenarios.This paper reviews several professional simulators and custom-built virtual environments that have been used for agricultural robotic applications.The key features and performance efficiency of three selected simulators were also compared.A simulation case study was demonstrated to highlight some of the powerful functionalities of the Virtual Robot Experimentation Platform.Details of the objects and scenes were presented as the proof-of-concept for using a completely simulated robotic platform and sensing systems in a virtual citrus orchard.It was shown that the simulated workspace can provide a configurable and modular prototype robotic system that is capable of adapting to several field conditions and tasks through easy testing and debugging of control algorithms with zero damage risk to the real robot and to the actual equipment.This review suggests that an open-source software platform for agricultural robotics will significantly accelerate effective collaborations between different research groups for sharing existing workspaces,algorithms,and reusing the materials.
