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An Unmanned Vehicle Obstacle Avoidance Method Based on Chance Constrained Model Predictive Control

A predictive control and constraint model technology, applied in the direction of adaptive control, general control system, control/regulation system, etc., can solve the problem of not considering the actual area occupied by the vehicle, not considering the uncertainty of the obstacle state, and the final model predictive control optimization Problems are not easy to find and other problems, to achieve the effect of ensuring safety and good environmental adaptability

Active Publication Date: 2019-12-31
TONGJI UNIV
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Problems solved by technology

However, the main disadvantage of this algorithm is that it does not consider the actual area occupied by the vehicle, and only regards the vehicle as a particle; it only considers the uncertainty of the vehicle state, and does not consider the uncertainty of the obstacle state
Since the substitution constraints are non-convex with respect to the decision variables, the final model predictive control optimization problem is not easy to solve

Method used

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  • An Unmanned Vehicle Obstacle Avoidance Method Based on Chance Constrained Model Predictive Control
  • An Unmanned Vehicle Obstacle Avoidance Method Based on Chance Constrained Model Predictive Control
  • An Unmanned Vehicle Obstacle Avoidance Method Based on Chance Constrained Model Predictive Control

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Embodiment

[0052] Such as figure 1 As shown, an unmanned vehicle obstacle avoidance method based on chance constraint model predictive control includes the following steps:

[0053] S1: Establish a vehicle dynamics model, which is used to describe the dynamic characteristics of unmanned vehicles:

[0054] The vehicle dynamics model is described as follows:

[0055]

[0056] Among them, the state vector and input vector are: with u=δ f , and Respectively represent the lateral velocity and longitudinal velocity in the body coordinate system, and the longitudinal velocity constant, is the roll angle, is the yaw rate, and respectively represent the lateral and longitudinal velocities in the global coordinate system, δ f is the front wheel rotation angle, a and b respectively represent the distance from the center of mass to the front axle, and the distance from the center of mass to the rear axle, C cf with C cr respectively represent the cornering stiffness of the fro...

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Abstract

The invention relates to an unmanned vehicle obstacle avoidance method based on prediction control of a chance constrained model, which comprises the steps of 1) building a kinetic model of an unmanned vehicle, and describing kinetic characteristics of the unmanned vehicle; 2) building a cost function and constraint conditions of a model prediction control optimization problem; and 3) solving the model prediction control optimization problem to obtain an optimal path for obstacle avoidance of the unmanned vehicle. Compared with the prior art, the unmanned vehicle obstacle avoidance method has the advantages of good environmental adaptability and ability of considering the actual occupied area of the vehicle.

Description

technical field [0001] The invention relates to the field of obstacle avoidance for unmanned vehicles, in particular to an obstacle avoidance method for unmanned vehicles based on chance constraint model predictive control. Background technique [0002] Due to the advantages of unmanned vehicles in reducing traffic accidents and casualties, alleviating and reducing traffic congestion, and reducing the energy consumed by users in driving, etc., they have received extensive attention from academia and industry. The implementation of unmanned vehicles involves various fields, including information and sensing technology, trajectory tracking technology and obstacle avoidance technology. It is of great significance to realize the obstacle avoidance of unmanned vehicles in various situations. Obstacle avoidance ability is the foundation of unmanned vehicles, and only unmanned vehicles with good obstacle avoidance ability can be truly practical. [0003] Unmanned vehicle obstacle...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04G05D1/02
CPCG05B13/048G05D1/0219
Inventor 王祝萍江厚杰张皓陈启军
Owner TONGJI UNIV
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