CN108227484A - Humanoid robot deflection moment control method - Google Patents
Humanoid robot deflection moment control method Download PDFInfo
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- CN108227484A CN108227484A CN201611194751.7A CN201611194751A CN108227484A CN 108227484 A CN108227484 A CN 108227484A CN 201611194751 A CN201611194751 A CN 201611194751A CN 108227484 A CN108227484 A CN 108227484A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 210000000544 articulatio talocruralis Anatomy 0.000 claims abstract description 27
- 238000005457 optimization Methods 0.000 claims abstract description 9
- 230000005021 gait Effects 0.000 claims description 15
- 210000002683 foot Anatomy 0.000 claims description 5
- 230000033001 locomotion Effects 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 2
- 210000003423 ankle Anatomy 0.000 abstract 1
- 238000005265 energy consumption Methods 0.000 abstract 1
- 230000001133 acceleration Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 3
- 230000005484 gravity Effects 0.000 description 2
- 210000003692 ilium Anatomy 0.000 description 2
- 238000013507 mapping Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 210000004233 talus Anatomy 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
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- Software Systems (AREA)
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- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
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Abstract
The invention discloses a method for controlling the deflection moment of a humanoid robot, which relates to a method for controlling the deflection moment compensation of the humanoid robot by adopting a biped walking mode; the method is characterized in that the method for controlling the deflection moment eliminates the influence of the deflection moment on the walking stability by controlling the ankle joint so as to minimize the equivalent effect of the ankle jointAnd establishing an optimization equation for the target, and obtaining the ankle joint position compensation offset by adopting an online iterative algorithm. The proposal fully considers the influence of energy consumption on the control performance, is suitable for the occasions such as an upper arm-free robot or a robot hand-held heavy object, and hasWide application range, small influence on the original walking posture and high energy efficiency.
Description
Technical field
The present invention relates to anthropomorphic robot control technology fields.Specifically, it is a kind of anthropomorphic robot yaw moment control
Method processed.
Background technology
Anthropomorphic robot is one of most popular research topic with forward position of current robot field, collects machinery, electronics, calculating
The multi-door subject such as machine, material, sensor, control technology and artificial intelligence is the important of national high-tech strength in one
Mark.Meanwhile anthropomorphic robot is more, complicated, coupling the is strong nonlinear system of a complicated degree of freedom, wherein walking
Row stability problem is the important Basic Problems in anthropomorphic robot field.Robot is in gait processes, due to each portion of body
Divide and do not move in the same plane, thus inevitably generate yaw moment, influence the equalising torque of vertical direction, and then
Influence walking stability.The mode of conventional method generally use double arm swing, ilium joint or waist joint rotation offsets yaw moment
Influence, the mode of double arm swing influences small and gait naturally, but being not suitable for portable without tow-armed robot or robot to gait
The occasions such as weight, and the energy that the mode of ilium joint or waist joint rotation consumes is larger, and has larger impact to original pose, this
A little shortcomings all constrain further applying for these methods.
Invention content
To solve the above problems, the technical solution adopted by the present invention is:By the way that ankle-joint is controlled to eliminate yaw moment to step
The influence of row stability supports sufficient stress model and to minimize ankle-joint equivalent force by establishingOptimization side is established for target
Journey 1, and ankle-joint location compensation offset is obtained using online iterative algorithm.
In said program, the support foot stress model as shown in Figure 1, point A represents ankle-joint,WithRespectively
Robot anklebone above section acts on the equivalent force and torque of ankle-joint in expression gait processes, and G points represent support foot
Position of centre of gravity, quality are, g is acceleration of gravity, and P represents resultant moment as zero point of zero moment,For ground
Face reaction force.
In said program, the support foot stress model makes stability trunk in gait processes and quadruped locomotion
Into influence be abstracted as the equivalent force that acts on ankle-jointAnd torque。
In above-mentioned scheme, the optimization method 1 is balanced by minimum ankle-joint angular acceleration and vertical direction torque
Condition forms, and optimization method is represented by：
（1）
Wherein,For equivalent force position vector, specially；VariableFor yaw momentWith equivalent force
SquareVertical componentThe sum of opposite number, i.e.,。
In above-mentioned scheme, the online iterative algorithm uses iteration inequality
GenerationTime series, whereinFor adjustable parameter,,ForWith mapping letter
NumberBetween error,WithRespectively equivalent forceThe upper bound of value range with
Lower bound,.When more than maximum iteration or, whereinFor it is adjustable most
Small error, then iteration stopping, is solved, and vectorFirst three component be equivalent forceValue.
In above-mentioned scheme, the ankle-joint location correct amount can be by the correction amount of ankle-joint accelerationIt calculates
It obtains, wherein,,WithThe respectively length and quality of shank.
The advantage of the invention is that：Only shadow of the yaw moment to walking stability is offset by the way that ankle-joint is controlled to reach
It rings, smaller is influenced on original walking, and can be suitable for occasions such as the portable weights of no arm robot or robot, having should
With the wider array of advantage of range.
Description of the drawings
Fig. 1 is the sufficient stress model of support.
Fig. 2 is two-dimentional walking discrete time gait figure.
The control of Fig. 3 yaw moments is front and rear to be compared.
Specific embodiment
The implementation process further illustrated the present invention with reference to the accompanying drawings and examples
As shown in Figure 1, the sufficient stress model figure of support according to the invention, by trunk in gait processes and quadruped locomotion to stability
Caused by influence to be abstracted as the equivalent force that acts on ankle-jointAnd torque, can be obtained by principle of moment balance,, wherein,Represent robot
Ankle-joint above section acts on the vertical component of ankle-joint resultant couple,Represent ankle-joint location coordinate,WithThe quality and acceleration of body parts are represented respectively,、、、Robot body parts matter is represented respectively
The acceleration of the x-axis of the heart, y-axis coordinate and respective direction.
In this example, according to robot walking equilibrium principle, the sufficient stress model of support is established, with ankle-joint angle equivalent forceMinimum target according to the optimization method 1 that the moment equilibrium condition of the sufficient stress model of support is established, and obtains equivalent force position
Vectorial W.It is as follows
Wherein, variable can obtain by vertical direction torque equilibrium conditionExpression formula be yaw momentWith equivalent moment
The sum of vertical component opposite number, i.e.,, equivalent force position vector。
In this example, the online iterative algorithm uses iteration inequality
GenerationTime series, whereinFor adjustable parameter,,ForWith mapping letter
NumberBetween error,WithRespectively equivalent forceThe upper bound of value range with
Lower bound,.When more than maximum iteration or, whereinFor it is adjustable most
Small error, then iteration stopping, is solved。
In this example, the ankle-joint location correct amount is by formulaIt is calculated, wherein,
The correct amount of ankle-joint acceleration is represented,WithThe respectively length and quality of shank.
Obtaining the correct amount of ankle-joint accelerationLater, the final angle of subsequent time ankle-joint can be finally obtained.
In the following, the performance of control method carried using the emulation experiment verification present invention, main emulation platform are used
Matlab 2010b versions.Entire gait processes include three kinds of gaits, are starting gait respectively, period walking gait, halt step
State, each walking period or so foot respectively steps out a step, and each period continues 1.2s.Its two-dimentional walking discrete time gait figure is as schemed
Shown in 2, yaw moment compares figure as shown in figure 3, wherein, solid line represents to use institute's extracting method control of the present invention in Fig. 3 before and after control
Later yaw moment is made, black double-crossed represents maximum static friction force torque, and dotted line represents the yaw moment before control, when inclined
When putting torque beyond maximum static friction force torque, robot will occur to break away, even fall down.
It can be seen that by simulation result, algorithm gait nature, smooth trajectory carried using the present invention, yaw moment is had
Effect control.
Claims (6)
1. a kind of anthropomorphic robot yaw moment control method, it is characterised in that：The yaw moment control method passes through control
Ankle-joint eliminates influence of the yaw moment to walking stability, and sufficient stress model is supported and to minimize ankle-joint etc. by establishing
EffectOptimization method 1 is established for target, ankle-joint location compensation offset is obtained using online iterative algorithm.
2. a kind of anthropomorphic robot yaw moment control method according to claim 1, which is characterized in that in gait processes
The yaw moment of generation is mainly by controlling ankle-joint to complete.
A kind of 3. anthropomorphic robot yaw moment control method according to claim 1, which is characterized in that the optimization side
1 method for building up of journey is as follows：According to robot walking equilibrium principle, the sufficient stress model of support is established, with ankle-joint equivalent forceMost
Small is optimization aim, the optimization method 1 established according to the moment equilibrium condition of the sufficient stress model vertical direction of support.
A kind of 4. anthropomorphic robot yaw moment control method according to claim 1, which is characterized in that the support foot
Trunk in gait processes and quadruped locomotion are influenced to be abstracted as to act on ankle-joint by portion's stress model caused by stability
Equivalent forceAnd torque。
5. a kind of anthropomorphic robot yaw moment control method according to claim 1, which is characterized in that described to change online
Iteration inequality is used for algorithmGenerationTime series, when more than greatest iteration
Number or, whereinFor adjustable minimal error, then iteration stopping, is solved, wherein, vectorFirst three component be equivalent forceValue.
A kind of 6. anthropomorphic robot yaw moment control method according to claim 1, which is characterized in that ankle-joint location
Correct amount can be by the correction amount of ankle-joint accelerationIt is calculated, and。
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| CN201611194751.7A CN108227484A (en) | 2016-12-22 | 2016-12-22 | Humanoid robot deflection moment control method |
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| CN201611194751.7A CN108227484A (en) | 2016-12-22 | 2016-12-22 | Humanoid robot deflection moment control method |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112488000A (en) * | 2020-12-02 | 2021-03-12 | 河北工业大学 | Modeling method and application of whole-body gait motion model with visual-touch fusion |
| CN113341698A (en) * | 2021-06-17 | 2021-09-03 | 仲恺农业工程学院 | Humanoid robot walking control method for adjusting joint angles of two legs based on neural network |
| CN113467246A (en) * | 2021-07-16 | 2021-10-01 | 浙江大学 | Yaw moment compensation method for biped robot |
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| CN103149933A (en) * | 2013-02-27 | 2013-06-12 | 南京邮电大学 | Closed-loop control-based humanoid robot omnidirectional walking method |
| US20150158175A1 (en) * | 2013-12-10 | 2015-06-11 | Samsung Electronics Co., Ltd. | Wearable robot and control method theorof |
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| KR20160146000A (en) * | 2015-06-11 | 2016-12-21 | 동아대학교 산학협력단 | Apparatus and method for controlling posture of humanoid robot |
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2016
- 2016-12-22 CN CN201611194751.7A patent/CN108227484A/en active Pending
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| CN103149933A (en) * | 2013-02-27 | 2013-06-12 | 南京邮电大学 | Closed-loop control-based humanoid robot omnidirectional walking method |
| US20150158175A1 (en) * | 2013-12-10 | 2015-06-11 | Samsung Electronics Co., Ltd. | Wearable robot and control method theorof |
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| YANG，LIANG等: "Adaptive Fuzzy Yaw Moment Control of Humanoid Robot Based On Ankle Joint", 《2015 34TH CHINESE CONTROL CONFERENCE (CCC) 》 * |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112488000A (en) * | 2020-12-02 | 2021-03-12 | 河北工业大学 | Modeling method and application of whole-body gait motion model with visual-touch fusion |
| CN112488000B (en) * | 2020-12-02 | 2022-08-09 | 河北工业大学 | Modeling method and application of whole-body gait motion model with visual-touch fusion |
| CN113341698A (en) * | 2021-06-17 | 2021-09-03 | 仲恺农业工程学院 | Humanoid robot walking control method for adjusting joint angles of two legs based on neural network |
| CN113467246A (en) * | 2021-07-16 | 2021-10-01 | 浙江大学 | Yaw moment compensation method for biped robot |
| CN113467246B (en) * | 2021-07-16 | 2023-10-20 | 浙江大学 | Offset moment compensation method for biped robot |
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Application publication date: 20180629 |