Movatterモバイル変換


[0]ホーム

URL:


CN106444381A - Power-saving robot - Google Patents

Power-saving robot
Download PDF

Info

Publication number
CN106444381A
CN106444381ACN201610936022.8ACN201610936022ACN106444381ACN 106444381 ACN106444381 ACN 106444381ACN 201610936022 ACN201610936022 ACN 201610936022ACN 106444381 ACN106444381 ACN 106444381A
Authority
CN
China
Prior art keywords
robot
path
module
fuzzy
power
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201610936022.8A
Other languages
Chinese (zh)
Inventor
彭建盛
何奇文
覃勇
彭金松
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hechi University
Original Assignee
Hechi University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hechi UniversityfiledCriticalHechi University
Priority to CN201610936022.8ApriorityCriticalpatent/CN106444381A/en
Publication of CN106444381ApublicationCriticalpatent/CN106444381A/en
Pendinglegal-statusCriticalCurrent

Links

Classifications

Landscapes

Abstract

Translated fromChinese

本发明公开了一种节电机器人,由于主要包括:路径优化模块、主控模块、行走机构和电源模块,所述路径优化模块和电源模块分别与主控模块连接,所述路径优化模块寻找最优路径,经主控模块控制行走机构,控制机器人行走,所述电源模块为路径优化模块和主控模块供电;从而实现的通过对行走机器人最优路径归还,节约机器人电量的优点。The invention discloses a power-saving robot, which mainly includes: a path optimization module, a main control module, a walking mechanism and a power supply module, the path optimization module and the power supply module are respectively connected with the main control module, and the path optimization module searches for the most The optimal path is controlled by the main control module to control the walking mechanism and the walking of the robot. The power supply module supplies power to the path optimization module and the main control module; thereby realizing the advantages of saving the power of the robot by returning the optimal path to the walking robot.

Description

Translated fromChinese
一种节电机器人A power-saving robot

技术领域technical field

本发明涉及机器人节电技术领域,具体地,涉及一种节电机器人。The invention relates to the technical field of robot power saving, in particular to a power saving robot.

背景技术Background technique

在利用机器人领域,普遍存在机器人耗电量大的缺陷,尤其是可行走机器人耗电量非常大。In the field of using robots, there is a common defect that robots consume a lot of power, especially walking robots consume a lot of power.

发明内容Contents of the invention

本发明的目的在于,针对上述问题,提出一种节电机器人,以实现的通过对行走机器人最优路径规划,节约机器人电量的优点。The object of the present invention is to propose a power-saving robot for the above problems, so as to realize the advantage of saving the power of the robot by planning the optimal path of the walking robot.

为实现上述目的,本发明采用的技术方案是:一种节电机器人,主要包括:路径优化模块、主控模块、行走机构和电源模块,所述路径优化模块和电源模块分别与主控模块连接,所述路径优化模块寻找最优路径,经主控模块控制行走机构,控制机器人行走,所述电源模块为路径优化模块和主控模块供电。In order to achieve the above object, the technical solution adopted in the present invention is: a power-saving robot, mainly comprising: a path optimization module, a main control module, a walking mechanism and a power supply module, and the path optimization module and the power supply module are respectively connected to the main control module , the path optimization module searches for the optimal path, controls the traveling mechanism through the main control module, and controls the robot to walk, and the power supply module supplies power to the path optimization module and the main control module.

进一步地,所述路径优化模块,寻找环境最短路径,当机器人在前进中检测到将与环境中的动态障碍物相碰,则视最短路径上离动态障碍物安全的栅格为局部目标点,确定动态障碍物的运动范围;机器人沿着信息素浓度大的栅格前进,得到一条避开动态障碍物且经过指定点的最优路径。Further, the path optimization module searches for the shortest path in the environment, and when the robot detects that it will collide with a dynamic obstacle in the environment while advancing, it regards the grid that is safe from the dynamic obstacle on the shortest path as a local target point, Determine the movement range of dynamic obstacles; the robot moves along the grid with high pheromone concentration, and obtains an optimal path that avoids dynamic obstacles and passes through the specified point.

进一步地,还包括多个机器人路径优化模块,具体包括根据模糊控制理论建立机器人运动的模糊控制器,并且确立模糊控制器的输入变量和输出变量;利用中确定的模糊控制器中的输入变量和输出变量,用语言描述出模糊控制器的输入变量和输出变量;根据模糊控制理论确立定性推理原则,根据迷糊控制器的输入信号和输出信号,建立模糊控制规则;选取各输入语言变量和输出语言变量的隶属度函数,即确定输入变量和输出变量的关系,使得在收到输入变量时计算得出输出变量;由上述过程求取得出的各个模糊变量,进行解模糊化,按照隶属度函数最大原则进行表决,对机器人进行相应的动作,完成单个机器人路径规划的任务;在上述基础上,将机器人看成是动态的前方障碍物,选取相对应的模糊规则,实现多机器人路径规划与协调避碰的任务。Further, it also includes a plurality of robot path optimization modules, specifically including establishing a fuzzy controller for robot motion according to fuzzy control theory, and establishing input variables and output variables of the fuzzy controller; using the input variables and output variables of the fuzzy controller determined in Output variables, using language to describe the input variables and output variables of the fuzzy controller; establish qualitative reasoning principles according to the fuzzy control theory, and establish fuzzy control rules according to the input and output signals of the fuzzy controller; select each input language variable and output language The membership function of the variable is to determine the relationship between the input variable and the output variable, so that the output variable is calculated when the input variable is received; each fuzzy variable obtained by the above process is defuzzified, and the maximum value of the membership function is Based on the above, the robot is regarded as a dynamic obstacle ahead, and the corresponding fuzzy rules are selected to realize multi-robot path planning and coordinated avoidance. touch task.

本发明各实施例的一种节电机器人,由于主要包括:路径优化模块、主控模块、行走机构和电源模块,所述路径优化模块和电源模块分别与主控模块连接,所述路径优化模块寻找最优路径,经主控模块控制行走机构,控制机器人行走,所述电源模块为路径优化模块和主控模块供电;从而实现的通过对行走机器人最优路径归还,节约机器人电量的优点。A kind of power-saving robot of each embodiment of the present invention, owing to mainly comprising: path optimization module, main control module, walking mechanism and power supply module, described path optimization module and power supply module are respectively connected with main control module, and described path optimization module Find the optimal path, control the walking mechanism through the main control module, and control the robot to walk, and the power supply module supplies power to the path optimization module and the main control module; thereby realizing the advantage of saving the power of the robot by returning the optimal path to the walking robot.

本发明的其它特征和优点将在随后的说明书中阐述,并且,部分地从说明书中变得显而易见,或者通过实施本发明而了解。Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention.

下面通过实施例,对本发明的技术方案做进一步的详细描述。The technical solutions of the present invention will be described in further detail below through examples.

具体实施方式detailed description

以下结合对本发明的优选实施例进行说明,应当理解,此处所描述的优选实施例仅用于说明和解释本发明,并不用于限定本发明。The preferred embodiments of the present invention will be described below in conjunction with it. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

具体地,一种节电机器人,主要包括:路径优化模块、主控模块、行走机构和电源模块,所述路径优化模块和电源模块分别与主控模块连接,所述路径优化模块寻找最优路径,经主控模块控制行走机构,控制机器人行走,所述电源模块为路径优化模块和主控模块供电。Specifically, a power-saving robot mainly includes: a path optimization module, a main control module, a traveling mechanism and a power supply module, the path optimization module and the power supply module are respectively connected to the main control module, and the path optimization module searches for the optimal path , controlling the walking mechanism through the main control module to control the walking of the robot, and the power supply module supplies power to the path optimization module and the main control module.

所述路径优化模块,寻找环境最短路径,当机器人在前进中检测到将与环境中的动态障碍物相碰,则视最短路径上离动态障碍物安全的栅格为局部目标点,确定动态障碍物的运动范围;机器人沿着信息素浓度大的栅格前进,得到一条避开动态障碍物且经过指定点的最优路径。The path optimization module searches for the shortest path in the environment, and when the robot detects that it will collide with a dynamic obstacle in the environment during its advancement, the grid that is safe from the dynamic obstacle on the shortest path is regarded as a local target point to determine the dynamic obstacle The range of motion of the object; the robot advances along the grid with high pheromone concentration, and obtains an optimal path that avoids dynamic obstacles and passes through the specified point.

还包括多个机器人路径优化模块,具体包括根据模糊控制理论建立机器人运动的模糊控制器,并且确立模糊控制器的输入变量和输出变量;利用中确定的模糊控制器中的输入变量和输出变量,用语言描述出模糊控制器的输入变量和输出变量;根据模糊控制理论确立定性推理原则,根据迷糊控制器的输入信号和输出信号,建立模糊控制规则;选取各输入语言变量和输出语言变量的隶属度函数,即确定输入变量和输出变量的关系,使得在收到输入变量时计算得出输出变量;由上述过程求取得出的各个模糊变量,进行解模糊化,按照隶属度函数最大原则进行表决,对机器人进行相应的动作,完成单个机器人路径规划的任务;在上述基础上,将机器人看成是动态的前方障碍物,选取相对应的模糊规则,实现多机器人路径规划与协调避碰的任务。It also includes multiple robot path optimization modules, specifically including establishing a fuzzy controller for robot motion based on fuzzy control theory, and establishing the input variables and output variables of the fuzzy controller; using the input variables and output variables in the fuzzy controller determined in the process, Describe the input variables and output variables of the fuzzy controller in language; establish the qualitative reasoning principle according to the fuzzy control theory, and establish the fuzzy control rules according to the input signal and output signal of the fuzzy controller; select the subordination of each input language variable and output language variable degree function, that is, to determine the relationship between the input variable and the output variable, so that the output variable is calculated when the input variable is received; each fuzzy variable obtained by the above process is defuzzified and voted according to the principle of the maximum membership degree function , perform corresponding actions on the robot to complete the task of path planning for a single robot; on the basis of the above, regard the robot as a dynamic obstacle ahead, select the corresponding fuzzy rules, and realize the task of multi-robot path planning and coordinated collision avoidance .

至少可以达到以下有益效果:克服现有技术行走机器人耗电量大的缺陷,实现通过对行走机器人最优路径归还,节约机器人电量的优点。At least the following beneficial effects can be achieved: overcoming the defect of large power consumption of the walking robot in the prior art, and realizing the advantage of saving the power of the robot by returning the optimal path of the walking robot.

最后应说明的是:以上所述仅为本发明的优选实施例而已,并不用于限制本发明,尽管参照前述实施例对本发明进行了详细的说明,对于本领域的技术人员来说,其依然可以对前述各实施例所记载的技术方案进行修改,或者对其中部分技术特征进行等同替换。凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。Finally, it should be noted that: the above is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, it still The technical solutions recorded in the foregoing embodiments may be modified, or some technical features thereof may be equivalently replaced. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (3)

Translated fromChinese
1.一种节电机器人,其特征在于,包括路径优化模块、主控模块、行走机构和电源模块,所述路径优化模块和电源模块分别与主控模块连接,所述路径优化模块寻找最优路径,经主控模块控制行走机构,控制机器人行走,所述电源模块为路径优化模块和主控模块供电。1. A power-saving robot, characterized in that it comprises a path optimization module, a main control module, a running gear and a power supply module, the path optimization module and the power supply module are respectively connected with the main control module, and the path optimization module searches for the optimal The path is controlled by the main control module to control the walking mechanism and the walking of the robot. The power supply module supplies power to the path optimization module and the main control module.2.根据权利要求1所述的节电机器人,其特征在于,所述路径优化模块,寻找环境最短路径,当机器人在前进中检测到将与环境中的动态障碍物相碰,则视最短路径上离动态障碍物安全的栅格为局部目标点,确定动态障碍物的运动范围;机器人沿着信息素浓度大的栅格前进,得到一条避开动态障碍物且经过指定点的最优路径。2. The power-saving robot according to claim 1, wherein the path optimization module searches for the shortest path in the environment, and when the robot detects that it will collide with a dynamic obstacle in the environment while advancing, the shortest path The grid that is safe from the dynamic obstacle is the local target point, and the movement range of the dynamic obstacle is determined; the robot moves along the grid with high pheromone concentration, and obtains an optimal path that avoids the dynamic obstacle and passes through the specified point.3.根据权利要求1所述的节电机器人,其特征在于,还包括多个机器人路径优化模块,具体包括根据模糊控制理论建立机器人运动的模糊控制器,并且确立模糊控制器的输入变量和输出变量;利用中确定的模糊控制器中的输入变量和输出变量,用语言描述出模糊控制器的输入变量和输出变量;根据模糊控制理论确立定性推理原则,根据迷糊控制器的输入信号和输出信号,建立模糊控制规则;选取各输入语言变量和输出语言变量的隶属度函数,即确定输入变量和输出变量的关系,使得在收到输入变量时计算得出输出变量;由上述过程求取得出的各个模糊变量,进行解模糊化,按照隶属度函数最大原则进行表决,对机器人进行相应的动作,完成单个机器人路径规划的任务;在上述基础上,将机器人看成是动态的前方障碍物,选取相对应的模糊规则,实现多机器人路径规划与协调避碰的任务。3. The power-saving robot according to claim 1, further comprising a plurality of robot path optimization modules, specifically including establishing a fuzzy controller for robot motion according to fuzzy control theory, and establishing the input variables and output of the fuzzy controller Variables; use the input variables and output variables in the fuzzy controller determined in the process, describe the input variables and output variables of the fuzzy controller in language; establish the qualitative reasoning principle according to the fuzzy control theory, according to the input signal and output signal of the fuzzy controller , to establish fuzzy control rules; select the membership function of each input language variable and output language variable, that is, determine the relationship between the input variable and the output variable, so that the output variable can be calculated when the input variable is received; the obtained by the above process Each fuzzy variable is defuzzified, voted according to the principle of maximum membership function, and performs corresponding actions on the robot to complete the task of path planning for a single robot; on the basis of the above, the robot is regarded as a dynamic obstacle ahead, and the selected The corresponding fuzzy rules realize the task of multi-robot path planning and coordination collision avoidance.
CN201610936022.8A2016-11-012016-11-01Power-saving robotPendingCN106444381A (en)

Priority Applications (1)

Application NumberPriority DateFiling DateTitle
CN201610936022.8ACN106444381A (en)2016-11-012016-11-01Power-saving robot

Applications Claiming Priority (1)

Application NumberPriority DateFiling DateTitle
CN201610936022.8ACN106444381A (en)2016-11-012016-11-01Power-saving robot

Publications (1)

Publication NumberPublication Date
CN106444381Atrue CN106444381A (en)2017-02-22

Family

ID=58177765

Family Applications (1)

Application NumberTitlePriority DateFiling Date
CN201610936022.8APendingCN106444381A (en)2016-11-012016-11-01Power-saving robot

Country Status (1)

CountryLink
CN (1)CN106444381A (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
CN101976079A (en)*2010-08-272011-02-16中国农业大学Intelligent navigation control system and method
CN103324196A (en)*2013-06-172013-09-25南京邮电大学Multi-robot path planning and coordination collision prevention method based on fuzzy logic
CN104808671A (en)*2015-05-192015-07-29东南大学Robot path planning method under home environment
CN105446339A (en)*2015-12-222016-03-30安徽工程大学Mobile robot path planning method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication numberPriority datePublication dateAssigneeTitle
CN101976079A (en)*2010-08-272011-02-16中国农业大学Intelligent navigation control system and method
CN103324196A (en)*2013-06-172013-09-25南京邮电大学Multi-robot path planning and coordination collision prevention method based on fuzzy logic
CN104808671A (en)*2015-05-192015-07-29东南大学Robot path planning method under home environment
CN105446339A (en)*2015-12-222016-03-30安徽工程大学Mobile robot path planning method

Similar Documents

PublicationPublication DateTitle
CN107168324B (en) A Robot Path Planning Method Based on ANFIS Fuzzy Neural Network
BlažičOn periodic control laws for mobile robots
CN106989748A (en)A kind of Agriculture Mobile Robot man-computer cooperation paths planning method based on cloud model
CN102521205B (en)Multi-Agent based robot combined search system by reinforcement learning
CN110209177A (en)Pilotless automobile control system and method based on model prediction and active disturbance rejection
CN103324196A (en)Multi-robot path planning and coordination collision prevention method based on fuzzy logic
KR102260529B1 (en) Robot motion control method based on map prediction
Guo et al.Optimal navigation for AGVs: A soft actor–critic-based reinforcement learning approach with composite auxiliary rewards
Zheng et al.Implicit trajectory planning for feedback linearizable systems: A time-varying optimization approach
CN115903806A (en) Multi-Agent Formation Obstacle Avoidance Method Based on Adaptive Dynamic Window Method
CN114063621A (en)Wheeled robot formation tracking and obstacle avoidance control method
CN105652874A (en)Mobile robot real-time obstacle avoiding method based on general wavefront algorithm
Xia et al.A reinforcement learning method of obstacle avoidance for industrial mobile vehicles in unknown environments using neural network
CN103713640A (en)Node movement behavior control method for mobile wireless sensor network
CN106444381A (en)Power-saving robot
Jin et al.Fuzzy logic system based obstacle avoidance for a mobile robot
Qian et al.Autonomous navigation for mobile robot based on a sonar ring and its implementation
LiuImproved Ant Colony Algorithm-based Automated Guided Vehicle Path Planning Research for Sensor-aware Obstacle Avoidance.
Resende et al.A new positioning and path following controller for unicycle mobile robots
Rajesh et al.Path Traversal and Obstacle Sensing Robot using Arduino
Benbouabdallah et al.A Behavior-Based Controller for a Mobile Robot Tracking a Moving Target in Multi-obstacles Environment
Xue et al.Foot-End Global Trajectory Planning via GCN-Based Heuristic Tree Search for Crossing Obstacles
Colledanchise et al.Robot navigation under uncertainties using event based sampling
He et al.Path planning for mobile robot based on fuzzy control
Zhang et al.Dynamic optimal formation control for mobile vehicles with minimizing communication path loss under topology switching

Legal Events

DateCodeTitleDescription
C06Publication
PB01Publication
C10Entry into substantive examination
SE01Entry into force of request for substantive examination
RJ01Rejection of invention patent application after publication

Application publication date:20170222

RJ01Rejection of invention patent application after publication

[8]ページ先頭

©2009-2025 Movatter.jp