CN112937563A - Unmanned vehicle obstacle avoidance method based on model predictive control - Google Patents
Unmanned vehicle obstacle avoidance method based on model predictive control Download PDFInfo
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- CN112937563A CN112937563A CN202110341724.2A CN202110341724A CN112937563A CN 112937563 A CN112937563 A CN 112937563A CN 202110341724 A CN202110341724 A CN 202110341724A CN 112937563 A CN112937563 A CN 112937563A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
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Abstract
The invention relates to the field of unmanned vehicle navigation, in particular to an unmanned vehicle obstacle avoidance method based on model predictive control, which comprises the following steps: s1, acquiring the shape of the front obstacle based on the infrared light curtain, and acquiring a relative distance parameter set between the front obstacle and the unmanned vehicle; s2, generating a corresponding obstacle avoiding ring based on the shape of the front obstacle and the relative distance parameter set between the front obstacle and the unmanned vehicle; s3, recognizing the gap between two adjacent obstacle avoiding rings based on the road generating model, and generating a corresponding unmanned vehicle passing road; and S4, planning the obstacle avoidance route of the unmanned vehicle by taking the generated unmanned vehicle passing road as a template and taking the shortest passing path as a target based on the obstacle avoidance route planning model. The invention can quickly acquire the global position information of the unmanned vehicle and the obstacle based on the infrared light curtain and the three-dimensional digital compass, thereby realizing the accurate obstacle avoidance of the unmanned vehicle.
Description
Technical Field
The invention relates to the field of unmanned vehicle navigation, in particular to an unmanned vehicle obstacle avoidance method based on model predictive control.
Background
The implementation of the unmanned vehicle relates to various fields, including information and sensing technology, trajectory tracking technology and obstacle avoidance technology. The obstacle avoidance method has very important significance in achieving obstacle avoidance of the unmanned vehicle under various conditions. The obstacle avoidance capability is the basis of the unmanned vehicle, and only the unmanned vehicle with good obstacle avoidance capability has the possibility of really having practicability.
At present, the existing unmanned vehicle obstacle avoidance method generally has the defects of complex calculation process and low accuracy.
Disclosure of Invention
In order to solve the technical problems, the invention provides an unmanned vehicle obstacle avoidance method based on model predictive control, global position information of an unmanned vehicle and an obstacle can be rapidly acquired based on an infrared light curtain and a three-dimensional digital compass, and therefore accurate obstacle avoidance of the unmanned vehicle can be realized.
In order to achieve the purpose, the invention adopts the technical scheme that:
an unmanned vehicle obstacle avoidance method based on model predictive control comprises the following steps:
s1, acquiring the shape of the front obstacle based on the infrared light curtain, and acquiring a relative distance parameter set between the front obstacle and the unmanned vehicle;
s2, generating a corresponding obstacle avoiding ring based on the shape of the front obstacle and the relative distance parameter set between the front obstacle and the unmanned vehicle;
s3, recognizing the gap between two adjacent obstacle avoiding rings based on the road generating model, and generating a corresponding unmanned vehicle passing road;
and S4, planning the obstacle avoidance route of the unmanned vehicle by taking the generated unmanned vehicle passing road as a template and taking the shortest passing path as a target based on the obstacle avoidance route planning model.
Further, in step S1, the infrared light curtain is in a fan shape of 60-90 degrees.
Further, in step S1, the current position of the center point of the unmanned vehicle is used as the origin of the three-dimensional coordinate system, the three-dimensional model of the unmanned vehicle is constructed, three-dimensional coordinates of all points on the front side of the three-dimensional model of the unmanned vehicle are obtained, the three-dimensional coordinates are used as the origin to calculate the relative distance between the unmanned vehicle and the obstacle in front, and a relative distance parameter set is obtained.
Further, in step S2, the shape parameters of the obstacle avoidance circle are obtained based on the shape of the front obstacle, and the three-dimensional coordinates of each point on the obstacle avoidance circle are obtained based on the relative distance parameter set between the front obstacle and the unmanned vehicle.
Further, in step S3, the generated unmanned vehicle passing road includes a shape of the road, each convex point and each concave point on both sides of the road, and coordinates of symmetrical points of each convex point and each concave point.
Further, in step S3, the three-dimensional coordinates of each point on two adjacent obstacle avoidance circles are recorded into the road generation model to identify the gap between the two adjacent obstacle avoidance circles, so as to generate a corresponding unmanned vehicle passing road.
Further, still include: and monitoring and identifying dynamic articles around the unmanned vehicle based on the image acquisition and identification module, and predicting the motion trail of the dynamic articles based on the dynamic article motion trail prediction model.
And further, planning the unmanned vehicle obstacle avoidance route by taking the generated unmanned vehicle passing road as a template, taking the shortest passing path as a target and taking the motion track prediction result of the dynamic article as a constraint condition on the basis of the obstacle avoidance route planning model.
Further, the current position of the center point of the unmanned vehicle is acquired in real time based on a three-dimensional digital compass.
The invention has the following beneficial effects:
the global position information of the unmanned vehicle and the obstacle can be rapidly acquired based on the infrared light curtain and the three-dimensional digital compass, the monitoring and the recognition of dynamic articles around the unmanned vehicle are realized in cooperation with the image acquisition and recognition module, the prediction of the motion track of the dynamic articles is realized based on the dynamic article motion track prediction model, and therefore the accurate obstacle avoidance of the unmanned vehicle can be realized.
Drawings
Fig. 1 is a flowchart of an unmanned vehicle obstacle avoidance method based on model predictive control according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of an unmanned vehicle obstacle avoidance method based on model predictive control according to embodiment 2 of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described in detail below with reference to examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example 1
As shown in fig. 1, an unmanned vehicle obstacle avoidance method based on model predictive control includes the following steps:
s1, acquiring the shape of the front obstacle based on the infrared light curtain, and acquiring a relative distance parameter set between the front obstacle and the unmanned vehicle;
s2, generating a corresponding obstacle avoiding ring based on the shape of the front obstacle and the relative distance parameter set between the front obstacle and the unmanned vehicle;
s3, recognizing the gap between two adjacent obstacle avoiding rings based on the road generating model, and generating a corresponding unmanned vehicle passing road;
and S4, planning the obstacle avoidance route of the unmanned vehicle by taking the generated unmanned vehicle passing road as a template and taking the shortest passing path as a target based on the obstacle avoidance route planning model.
In this embodiment, in step S1, the infrared light curtain is in a fan shape of 60-90 degrees.
In this embodiment, in step S1, the current position of the center point of the unmanned vehicle is used as the origin of the three-dimensional coordinate system, a three-dimensional model of the unmanned vehicle is constructed, three-dimensional coordinates of all points on the front side of the three-dimensional model of the unmanned vehicle (one point is taken every 5 ° with the origin of the three-dimensional coordinate system as the center of circle, and one point is arranged at each salient point) are obtained, the relative distance between the front obstacle and the unmanned vehicle is calculated with the three-dimensional coordinates as the origin, and the relative distance parameter set is obtained.
In this embodiment, in the step S2, the shape parameter of the obstacle avoidance circle is obtained based on the shape of the front obstacle, and the three-dimensional coordinate of each point on the obstacle avoidance circle is obtained based on the relative distance parameter set between the front obstacle and the unmanned vehicle (the current position of the center point of the unmanned vehicle is the origin of the three-dimensional coordinate system).
In this embodiment, in step S3, the generated unmanned vehicle passing road includes a shape of the road, each convex point and each concave point on two sides of the road, and coordinates of symmetrical points of each convex point and each concave point.
In this embodiment, in step S3, the three-dimensional coordinates of each point on two adjacent obstacle avoidance circles are recorded into the road generation model to identify the gap between the two adjacent obstacle avoidance circles, so as to generate a corresponding unmanned vehicle passing road.
In this embodiment, the current position of the center point of the unmanned vehicle is acquired in real time based on the three-dimensional digital compass.
Example 2
As shown in fig. 2, an unmanned vehicle obstacle avoidance method based on model predictive control includes the following steps:
s1, acquiring the shape of the front obstacle based on the infrared light curtain, and acquiring a relative distance parameter set between the front obstacle and the unmanned vehicle;
s2, generating a corresponding obstacle avoiding ring based on the shape of the front obstacle and the relative distance parameter set between the front obstacle and the unmanned vehicle;
s3, recognizing the gap between two adjacent obstacle avoiding rings based on the road generating model, and generating a corresponding unmanned vehicle passing road;
s4, monitoring and identifying dynamic articles around the unmanned vehicle based on the image acquisition and identification module, and predicting the motion trail of the dynamic articles based on the dynamic article motion trail prediction model;
s5, planning the unmanned vehicle obstacle avoidance route by taking the generated unmanned vehicle passing road as a template, the shortest passing path as a target and the motion trail prediction result of the dynamic article as a constraint condition on the basis of the obstacle avoidance route planning model.
In this embodiment, in step S1, the infrared light curtain is in a fan shape of 60-90 degrees.
In this embodiment, in step S1, the current position of the center point of the unmanned vehicle is used as the origin of the three-dimensional coordinate system, a three-dimensional model of the unmanned vehicle is constructed, three-dimensional coordinates of all points on the front side of the three-dimensional model of the unmanned vehicle (one point is taken every 5 ° with the origin of the three-dimensional coordinate system as the center of circle, and one point is arranged at each salient point) are obtained, the relative distance between the front obstacle and the unmanned vehicle is calculated with the three-dimensional coordinates as the origin, and the relative distance parameter set is obtained.
In this embodiment, in the step S2, the shape parameter of the obstacle avoidance circle is obtained based on the shape of the front obstacle, and the three-dimensional coordinate of each point on the obstacle avoidance circle is obtained based on the relative distance parameter set between the front obstacle and the unmanned vehicle (the current position of the center point of the unmanned vehicle is the origin of the three-dimensional coordinate system).
In this embodiment, in step S3, the generated unmanned vehicle passing road includes a shape of the road, each convex point and each concave point on two sides of the road, and coordinates of symmetrical points of each convex point and each concave point.
In this embodiment, in step S3, the three-dimensional coordinates of each point on two adjacent obstacle avoidance circles are recorded into the road generation model to identify the gap between the two adjacent obstacle avoidance circles, so as to generate a corresponding unmanned vehicle passing road.
In this embodiment, the current position of the center point of the unmanned vehicle is acquired in real time based on the three-dimensional digital compass.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be construed as the protection scope of the present invention.
Claims (9)
1. An unmanned vehicle obstacle avoidance method based on model predictive control is characterized by comprising the following steps:
s1, acquiring the shape of the front obstacle based on the infrared light curtain, and acquiring a relative distance parameter set between the front obstacle and the unmanned vehicle;
s2, generating a corresponding obstacle avoiding ring based on the shape of the front obstacle and the relative distance parameter set between the front obstacle and the unmanned vehicle;
s3, recognizing the gap between two adjacent obstacle avoiding rings based on the road generating model, and generating a corresponding unmanned vehicle passing road;
and S4, planning the obstacle avoidance route of the unmanned vehicle by taking the generated unmanned vehicle passing road as a template and taking the shortest passing path as a target based on the obstacle avoidance route planning model.
2. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: in step S1, the infrared light curtain is in the shape of a fan of 60-90 degrees.
3. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: in step S1, a three-dimensional model of the unmanned vehicle is constructed with the current position of the center point of the unmanned vehicle as the origin of the three-dimensional coordinate system, three-dimensional coordinates of all points on the front side of the three-dimensional model of the unmanned vehicle are obtained, the relative distance between the unmanned vehicle and the obstacle in front close to the unmanned vehicle is calculated with the three-dimensional coordinates as the starting points, and a relative distance parameter set is obtained.
4. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: in step S2, a shape parameter of the obstacle avoidance circle is obtained based on the shape of the front obstacle, and a three-dimensional coordinate of each point on the obstacle avoidance circle is obtained based on a relative distance parameter set between the front obstacle and the unmanned vehicle.
5. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: in step S3, the generated unmanned vehicle passing road includes the shape of the road, each convex point and each concave point on both sides of the road, and the coordinates of the symmetrical points of each convex point and each concave point.
6. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: in the step S3, the three-dimensional coordinates of each point on two adjacent obstacle avoidance circles are recorded into the road generation model to identify the gap between the two adjacent obstacle avoidance circles, so as to generate a corresponding unmanned vehicle passing road.
7. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 1, wherein: further comprising: and monitoring and identifying dynamic articles around the unmanned vehicle based on the image acquisition and identification module, and predicting the motion trail of the dynamic articles based on the dynamic article motion trail prediction model.
8. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 7, wherein: and planning the unmanned vehicle obstacle avoidance route based on the obstacle avoidance route planning model by taking the generated unmanned vehicle passing road as a template, the shortest passing path as a target and the motion trail prediction result of the dynamic article as a constraint condition.
9. The model predictive control-based unmanned vehicle obstacle avoidance method of claim 3, wherein: the current position of the center point of the unmanned vehicle is acquired in real time based on a three-dimensional digital compass.
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| CN115164931A (en) * | 2022-09-08 | 2022-10-11 | 南开大学 | System, method and equipment for assisting blind people in going out |
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Application publication date: 20210611 |