CN109514563B - Adaptive anti-noise redundant manipulator motion planning method - Google Patents

Adaptive anti-noise redundant manipulator motion planning method Download PDF

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CN109514563B
CN109514563B CN201910016168.4A CN201910016168A CN109514563B CN 109514563 B CN109514563 B CN 109514563B CN 201910016168 A CN201910016168 A CN 201910016168A CN 109514563 B CN109514563 B CN 109514563B
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noise
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motion planning
mechanical arm
dynamic system
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CN109514563A (en
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郭东生
蔡建煌
李泽昕
冯庆山
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Huaqiao University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00—Programme-controlled manipulators
    • B25J9/16—Programme controls
    • B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning

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Abstract

The invention provides a self-adaptive anti-noise redundant manipulator motion planning method, which utilizes an internal model principle to design a dynamic system capable of automatically generating a signal for compensating noise disturbance; based on the dynamic system, the feedback of position errors is introduced in combination with the requirements of mechanical arm motion planning, and a self-adaptive anti-noise motion planning scheme is established; and the lower computer controller drives the mechanical arm to effectively complete the given terminal planning task according to the solution result of the planning scheme. The motion planning scheme designed based on the internal model principle and the dynamic system can automatically calculate and obtain a signal for compensating noise disturbance according to the frequency of the harmonic noise, so that the redundant manipulator can still successfully complete a given terminal planning task under the condition of harmonic noise, and the method has important significance and value for self-adaptive anti-noise planning of the manipulator in practical application.

Description

Adaptive anti-noise redundant manipulator motion planning method
Technical Field
The invention relates to a self-adaptive anti-noise redundant manipulator motion planning method.
Background
The redundant manipulator is a mechanical device with an active tail end and is widely applied to national economic production activities such as industrial automation and the like. As an important issue in the application research of the mechanical arm, motion planning of the mechanical arm means that a trajectory of a joint variable of the mechanical arm is obtained by real-time solution according to a motion trajectory expected by an end effector (i.e., a given end planning task). At present, a plurality of effective motion planning schemes are proposed and applied to the mechanical arm, but the schemes almost do not consider the interference of noise. Obviously, in the presence of noise, the solution will fail and the robotic arm will not be able to complete a given end planning task. Noise, particularly harmonic noise, is often encountered in engineering applications, although motion planning of robotic arms is no exception; also, many industrially present noises can be converted into harmonic noises by fourier transform. Therefore, it is necessary and practical to consider and compensate the disturbance of harmonic noise in the robot arm motion planning
Disclosure of Invention
The invention aims to overcome the defects of the existing method and show the potential design of a future noise-tolerant method, and provides a self-adaptive anti-noise redundant manipulator motion planning method.
The invention adopts the following technical scheme:
a self-adaptive anti-noise redundant manipulator motion planning method is characterized in that a dynamic system capable of automatically generating signals for compensating noise disturbance is designed by utilizing an internal model principle; based on the dynamic system, the feedback of position errors is introduced in combination with the requirements of mechanical arm motion planning, and a self-adaptive anti-noise motion planning scheme is established; and the lower computer controller drives the mechanical arm to effectively complete the given terminal planning task under the condition of harmonic noise according to the solution result of the planning scheme.
The harmonic noise at the known frequency is described as:
δ(t)＝Asin(2πft+φ)
where A represents the amplitude of the noise, f represents the frequency of the noise, and φ represents the phase of the noise.
The dynamic system is designed to:
Figure BDA0001939144200000021
where y (t) represents the signal used to compensate for harmonic noise disturbances, and z (t) represents the time derivative of y (t) and is defined as
Figure BDA0001939144200000022
Figure BDA0001939144200000023
Denotes the time derivative of z (t).
The adaptive noise-resistant motion planning scheme is designed to:
Figure BDA0001939144200000024
wherein
Figure BDA0001939144200000025
Representing a joint speed of the mechanical arm; p (t) represents a pseudo-inverse matrix of a jacobian matrix J (θ (t)) of the robot arm, and θ (t) represents a joint angle of the robot arm; e (t) represents the position error in the mechanical arm motion planning process and is defined as
Figure BDA0001939144200000026
Figure BDA0001939144200000027
Representing a non-linear mapping function, rd(t) represents a desired motion trajectory of the end effector of the robotic arm;
Figure BDA0001939144200000028
is represented by rdThe time derivative of (t), γ represents the feedback gain for the position error, and t represents time.
As can be seen from the above description of the present invention, compared with the prior art, the present invention has the following advantages:
the invention provides a motion planning method which can automatically calculate and obtain a signal for compensating noise disturbance according to the frequency of harmonic noise so that a redundancy mechanical arm can still complete a given terminal planning task under the condition of harmonic noise; the method has important significance and value for self-adaptive noise-resistant planning of the mechanical arm in practical application.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is further described below by means of specific embodiments.
The adaptive anti-noise redundant manipulator motion planning method shown in fig. 1 mainly comprises six parts, namely detecting harmonic noise 1 with known frequency in manipulator planning, designing a dynamic system 2 for automatically compensating noise disturbance, feeding back 3 of motion planning requirements and position errors, establishing an adaptive anti-noise motion planning scheme 4, a lower computer controller 5 and a redundant manipulator 6.
Firstly, considering harmonic noise with known frequency in the mechanical arm planning process, and designing a dynamic system capable of automatically generating a signal for compensating noise disturbance by using an internal model principle; then based on the dynamic system, combining the requirements of mechanical arm motion planning, introducing feedback of position errors, and establishing a self-adaptive anti-noise motion planning scheme; and finally, the lower computer controller uses the solution result of the motion planning scheme for driving each joint of the mechanical arm so that the mechanical arm can still complete the given end planning task under the condition of harmonic noise.
Considering the harmonic noise δ (t) of known frequency existing in the mechanical arm planning process, the mathematical expression is described as:
δ(t)＝Asin(2πft+φ) (1)
where A represents the amplitude of the noise, f represents the frequency of the noise, and φ represents the phase of the noise. For this harmonic noise, both the amplitude a and the phase phi are unknown (or undetected), and only the frequency f is known (or detectable).
For the harmonic noise δ (t) in (1), using the principle of internal model, a dynamic system can be designed that can automatically generate a signal for compensating the harmonic noise disturbance as follows:
Figure BDA0001939144200000041
where y (t) represents the signal used to compensate for harmonic noise disturbances, and z (t) represents the time derivative of y (t) and is defined as
Figure BDA0001939144200000042
Figure BDA0001939144200000043
Denotes the time derivative of z (t).
Based on the dynamic system (2), the following self-adaptive anti-noise motion planning scheme can be established by introducing the feedback of position errors in combination with the requirements of mechanical arm motion planning:
Figure BDA0001939144200000044
wherein
Figure BDA0001939144200000045
Representing a joint speed of the mechanical arm; p (t) represents a pseudo-inverse matrix of a jacobian matrix J (θ (t)) of the robot arm, and θ (t) represents a joint angle of the robot arm; e (t) represents the position error in the mechanical arm motion planning process and is defined as
Figure BDA0001939144200000046
Figure BDA0001939144200000047
Representing a non-linear mapping function, rd(t) represents a desired motion trajectory of the end effector of the robotic arm;
Figure BDA0001939144200000048
is represented by rdThe time derivative of (t), γ represents the feedback gain for the position error, and t represents time.
The first dynamic equation in the established motion planning scheme (3) can be calculated in real time to obtain the T e [0, T ] of each moment]Joint speed for planning mechanical arm movement
Figure BDA0001939144200000049
And a joint angle θ (T), where T represents a period of the robotic arm motion plan; the second dynamic equation and the third dynamic equation can jointly calculate a signal y (t) for compensating the disturbance of the harmonic noise delta (t) in real time, namely-y (t) + delta (t) → 0, so that the first dynamic equation in (3) avoids the interference of the harmonic noise in the calculation process; therefore, the aim of self-adaption noise resistance in the mechanical arm motion planning process is fulfilled.
After the joint variables for planning the movement of the mechanical arm are obtained by solving in real time by using the scheme (3), the corresponding results are transmitted to the lower computer controller to drive each joint of the mechanical arm to move, so that the mechanical arm can still complete the given end planning task under the condition of harmonic noise.
The above description is only an embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications made by using the design concept should fall within the scope of infringing the present invention.

Claims (2)

1. A self-adaptive anti-noise redundant manipulator motion planning method is characterized in that a dynamic system capable of automatically generating signals for compensating noise disturbance is designed by utilizing an internal model principle, and the dynamic system is designed as follows:
Figure FDA0003101598080000011
where y (t) represents the signal used to compensate for harmonic noise disturbances, and z (t) represents the time derivative of y (t) and is defined as
Figure FDA0003101598080000012
Figure FDA0003101598080000013
Denotes the time derivative of z (t), f denotes the frequency of the noise; based on the dynamic system, the feedback of position errors is introduced by combining the requirements of mechanical arm motion planning, and a self-adaptive anti-noise motion planning scheme is established, which comprises the following steps:
Figure FDA0003101598080000014
wherein
Figure FDA0003101598080000015
Representing a joint speed of the mechanical arm; p (t) represents a pseudo-inverse matrix of a jacobian matrix J (θ (t)) of the robot arm, and θ (t) represents a joint angle of the robot arm; e (t) denotes the robot armPosition error in the dynamic planning process and is defined as
Figure FDA0003101598080000016
Figure FDA0003101598080000017
Representing a non-linear mapping function, rd(t) represents a desired motion trajectory of the end effector of the robotic arm;
Figure FDA0003101598080000018
is represented by rd(t), γ represents the feedback gain for the position error, t represents time; and the lower computer controller drives the mechanical arm to effectively complete the given terminal planning task under the condition of harmonic noise according to the solution result of the planning scheme.
2. The adaptive noise immune redundant robotic arm motion planning method of claim 1, wherein harmonic noise of known frequency is described as:
δ(t)＝A sin(2πft+φ)
where a represents the amplitude of the noise and phi the phase of the noise.
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CN111890363B (en) * 2020-07-27 2022-12-30 四川大学 Mechanical arm motion planning method based on rapid self-adaptive gradient neural network algorithm
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106737670A (en) * 2016-12-15 2017-05-31 华侨大学 A kind of repetitive motion planning method for redundant manipulator with noiseproof feature
CN106945041A (en) * 2017-03-27 2017-07-14 华南理工大学 A kind of repetitive motion planning method for redundant manipulator
CN107351081A (en) * 2017-06-27 2017-11-17 华侨大学 Redundancy mechanical arm impact degree layer motion planning method with speed-optimization characteristic
CN108015763A (en) * 2017-11-17 2018-05-11 华南理工大学 A kind of redundancy mechanical arm paths planning method of anti-noise jamming
CN109129486A (en) * 2018-09-26 2019-01-04 华南理工大学 A kind of repetitive motion planning method for redundant manipulator inhibiting periodic noise

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JP5979960B2 (en) * 2012-05-01 2016-08-31 キヤノン株式会社 Control device, control method and program

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106737670A (en) * 2016-12-15 2017-05-31 华侨大学 A kind of repetitive motion planning method for redundant manipulator with noiseproof feature
CN106945041A (en) * 2017-03-27 2017-07-14 华南理工大学 A kind of repetitive motion planning method for redundant manipulator
CN107351081A (en) * 2017-06-27 2017-11-17 华侨大学 Redundancy mechanical arm impact degree layer motion planning method with speed-optimization characteristic
CN108015763A (en) * 2017-11-17 2018-05-11 华南理工大学 A kind of redundancy mechanical arm paths planning method of anti-noise jamming
CN109129486A (en) * 2018-09-26 2019-01-04 华南理工大学 A kind of repetitive motion planning method for redundant manipulator inhibiting periodic noise

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