


技术领域technical field
本发明涉及一种面向无人飞行汽车、无人旋翼飞机等空间移动平台的空间感知安全技术领域,尤其涉及一种基于势能场的空间感知安全形式化方法,可用于风险预警、轨迹规划、智能决策等方向。The invention relates to the technical field of space perception security for space mobile platforms such as unmanned flying vehicles and unmanned rotorcraft, and in particular to a formalized method for space perception security based on potential energy fields, which can be used for risk warning, trajectory planning, intelligent direction of decision making.
背景技术Background technique
近年来,随着具有高效灵活、不受地形地势影响等优点的空间移动平台快速发展,其越来越多的应用于军事侦察、矿场勘测、灾区救援、民用摄影等领域,并得到了优异的应用效果。目前,空间移动平台正朝着高度智能化、无人化的方向发展,因此保证空间移动平台的安全性科研人员及各大制造厂商需首要解决的技术难题。保证空间移动平台安全性的首要任务是建立三维空间内的安全形式化方法,人工势场法可以描述出目标交通参与者对周围环境产生的危险程度的方法,被广泛应用在智能机器人避障寻迹、自动驾驶汽车轨迹规划等功能中,而目前人工势场法通常应用在道路平面内的二维空间上,并不适用于空间移动平台的三维空间。In recent years, with the rapid development of space mobile platforms with the advantages of high efficiency, flexibility, and no influence of terrain and terrain, it has been more and more used in military reconnaissance, mine survey, disaster area rescue, civilian photography and other fields, and has received excellent results. application effect. At present, the space mobile platform is developing towards a highly intelligent and unmanned direction. Therefore, ensuring the safety of the space mobile platform is a technical problem that researchers and major manufacturers need to solve first. The primary task to ensure the safety of space mobile platforms is to establish a formalized method for safety in three-dimensional space. The artificial potential field method can describe the degree of danger to the surrounding environment caused by target traffic participants, and is widely used in intelligent robot obstacle avoidance and search. However, the current artificial potential field method is usually applied to the two-dimensional space in the road plane, and is not suitable for the three-dimensional space of the space mobile platform.
发明内容Contents of the invention
本发明的目的在于克服现有技术缺陷,提出了一种基于势能场的空间感知安全形式化方法。The purpose of the present invention is to overcome the defects of the prior art, and propose a formalized method for space perception security based on a potential energy field.
为了实现上述目的,本发明提出了一种基于势能场的空间感知安全形式化方法,所述方法包括:In order to achieve the above object, the present invention proposes a formalized method for space perception security based on a potential energy field, the method comprising:
根据空间移动平台的运动速度,建立基于人工势场的无障碍物初始安全场;According to the movement speed of the space mobile platform, an obstacle-free initial safety field based on the artificial potential field is established;
确定空间移动平台设定范围内的障碍物状态;Determine the obstacle status within the set range of the space mobile platform;
根据障碍物状态,结合空间移动平台与移动障碍物的相对速度,建立基于人工势场的风险场;According to the state of the obstacle, combined with the relative speed of the space mobile platform and the moving obstacle, the risk field based on the artificial potential field is established;
将无障碍物的初始安全场和基于人工势场的风险场进行叠加,得到空间移动平台设定范围内的安全场。The initial safety field without obstacles and the risk field based on the artificial potential field are superimposed to obtain the safety field within the set range of the space mobile platform.
作为上述方法的一种改进,所述根据空间移动平台的运动速度,建立基于人工势场的无障碍物初始安全场;具体包括:As an improvement of the above method, the establishment of an obstacle-free initial safety field based on an artificial potential field according to the movement speed of the space mobile platform; specifically includes:
以空间移动平台的质心为三维坐标系的原点,根据空间移动平台的运动速度建立无障碍物的初始安全场S1,具体满足下式:Taking the center of mass of the space mobile platform as the origin of the three-dimensional coordinate system, according to the movement speed of the space mobile platform Establish an initial safety field S1 without obstacles, which specifically satisfies the following formula:
其中,表示移动平台附近无障碍物时的安全程度与运动速度模的分量负相关。in, Indicates the safety degree and movement speed when there are no obstacles near the mobile platform The components of the modulus are negatively correlated.
作为上述方法的一种改进,所述障碍物状态包括:第i个障碍物的质心坐标Pi、障碍物的质量mi和障碍物相对空间移动平台的速度As an improvement of the above method, the obstacle state includes: the barycenter coordinate Pi of the i-th obstacle, the mass mi of the obstacle, and the velocity of the obstacle relative to the space mobile platform
作为上述方法的一种改进,所述根据障碍物状态,结合空间移动平台与移动障碍物的相对速度,建立基于人工势场的风险场;具体包括:As an improvement of the above method, the risk field based on the artificial potential field is established according to the state of the obstacle, combined with the relative speed of the space mobile platform and the moving obstacle; specifically includes:
根据第i个障碍物的质心坐标Pi、障碍物的质量mi和障碍物相对空间移动平台的速度建立第i个障碍物基于人工势场的风险场Si满足下式:According to the centroid coordinates Pi of the i-th obstacle, the mass mi of the obstacle and the velocity of the obstacle relative to the space mobile platform The establishment of the i-th obstacle based on the risk field Si of the artificial potential field satisfies the following formula:
其中,k表示质量系数,θi与表示以Pi为原点的球极坐标系的两个方位角,μ1i,μ2i分别表示θi与的期望,σ1i,σ2i分别表示θi与的均方差,ρ表示θi与的相关系数。Among them, k represents the quality coefficient, θi and Indicates the two azimuth angles of the spherical polar coordinate system with Pi as the origin, μ1i and μ2i represent θi and The expectation of , σ1i , σ2i represent θi and The mean square error of , ρ means θi and correlation coefficient.
作为上述方法的一种改进,所述空间移动平台设定范围内的安全场S满足下式:As an improvement of the above method, the safety field S within the set range of the space mobile platform satisfies the following formula:
S=S1+∑SiS=S1+ ∑Si
其中,S1为无障碍物的初始安全场,Si为第i个障碍物基于人工势场的风险场与现有技术相比,本发明的优势在于:Among them, S1 is the initial safety field without obstacles, and Si is the risk field of the i-th obstacle based on the artificial potential field. Compared with the prior art, the advantages of the present invention are:
1、由于低空环境复杂且存在较多不可预测的障碍物,城市中的障碍物尤其是动态车辆会严重威胁飞行安全,特别是对于空间移动平台来说,更需要认知的是在危险情况下高动态障碍物的识别与预测,而目前这方面的研究成果尚少;1. Because the low-altitude environment is complex and there are many unpredictable obstacles, obstacles in the city, especially dynamic vehicles, will seriously threaten flight safety. Especially for space mobile platforms, what needs to be recognized is in dangerous situations Identification and prediction of highly dynamic obstacles, but there are still few research results in this area;
2、为保证系统安全性,空间立体感知是首要解决的技术难题,空间立体感知技术即当障碍物等信息被多个传感器采集到后,会生成一个空间型的信息并主动发送到车辆的规划控制模块进行统一的计算、分析和判断,目前,主要的立体感知方法集中于在三维空间内的建立人工势场,用于描述目标交通参与者对周围环境产生的影响,被广泛应用在智能机器人避障寻迹、自动驾驶汽车轨迹规划等功能中,而现有的人工势场法通常应用在道路平面内的二维空间上,并不适用于三维空间,因此,本发明创新性地构建一种立体空间感知场将为解决上述难点问题提供一种新的科学方法;2. In order to ensure the safety of the system, spatial stereoscopic perception is the primary technical problem to be solved. The spatial stereoscopic perception technology means that when information such as obstacles is collected by multiple sensors, a spatial type of information will be generated and actively sent to the planning of the vehicle. The control module performs unified calculation, analysis and judgment. At present, the main three-dimensional perception method focuses on establishing an artificial potential field in three-dimensional space, which is used to describe the impact of target traffic participants on the surrounding environment, and is widely used in intelligent robots. In functions such as obstacle avoidance and tracking, automatic driving vehicle trajectory planning, etc., the existing artificial potential field method is usually applied to the two-dimensional space in the road plane, and is not suitable for three-dimensional space. Therefore, the present invention innovatively constructs a A three-dimensional space perception field will provide a new scientific method to solve the above difficult problems;
3、本发明所提出的空间感知安全形式化方法,通过组合初始安全场和障碍物风险场,将叠加组合成的包络面凹凸程度作为判定周围的安全程度的标准,具有运算量较小、直观、实时更新等优点。3. The space perception safety formalization method proposed by the present invention combines the initial safety field and the obstacle risk field, and uses the concavo-convex degree of the superimposed and combined envelope surface as the standard for judging the safety degree of the surrounding area, which has a small amount of computation, Intuitive, real-time update and other advantages.
附图说明Description of drawings
图1是采用本发明的方法构建的初始安全场示意图;Fig. 1 is the initial safe field schematic diagram that adopts the method construction of the present invention;
图2是采用本发明的方法构建的相对空间移动平台速度低时的安全场示意图;Fig. 2 is the safe field schematic diagram when adopting the method of the present invention to construct when the relative space mobile platform speed is low;
图3是采用本发明的方法构建的相对空间移动平台速度高时的安全场示意图。Fig. 3 is a schematic diagram of the safety field constructed by the method of the present invention when the speed of the relative space mobile platform is high.
具体实施方式Detailed ways
基于人工势能法表示空间移动平台周围安全程度的方法。具体步骤如下:A method to express the safety degree around the space mobile platform based on the artificial potential energy method. Specific steps are as follows:
步骤1:确定空间移动平台的飞行速度Step 1: Determine the flight speed of the space mobile platform
步骤2:根据空间移动平台的飞行速度使用人工势场模型S1表示附近无障碍物时飞行器周围的安全程度,安全程度与速度模的分量负相关。Step 2: Move the platform's flight speed according to the space Use the artificial potential field modelS1 to represent the safety degree around the aircraft when there are no obstacles nearby, safety degree and speed The components of the modulus are negatively correlated.
步骤3:确定空间移动平台附近障碍物的状态,包括质心坐标Pi,障碍物的质量mi,和相对飞行器的速度Step 3: Determine the status of obstacles near the space mobile platform, including the coordinates of the center of mass Pi , the mass mi of the obstacle, and the relative velocity of the aircraft
步骤4:根据附近障碍物的状态,用人工势场模型Si表示障碍物对空间移动平台周围安全程度的风险影响。Step 4: According to the state of nearby obstacles, use the artificial potential field model Si to represent the risk impact of obstacles on the safety around the space mobile platform.
步骤5:将步骤2和步骤4的人工势场模型S1和Si叠加,即可得到空间移动平台周围的安全场S。Step 5: By superimposing the artificial potential field models S1 and Si in Step 2 and Step 4, the safety field S around the space mobile platform can be obtained.
S=S1+∑SiS=S1 +∑Si
下面结合附图和实施例对本发明的技术方案进行详细的说明。The technical solutions of the present invention will be described in detail below in conjunction with the drawings and embodiments.
实施例1Example 1
根据空间移动平台存在的三维环境中避障、安全评估等特殊行驶条件,本发明提出了基于人工势场的空间移动平台安全场的一种建立方法。安全场是用来评估其静止或空间运动状态时周围环境监视范围内不同方向的安全程度的人工势能场,有运算量较小、直观、实时更新等优点。人类驾驶员可以较早地看到某些方向存在障碍物并感知到这些方向比其他方向安全程度更低,建立安全场后,空间移动平台也可以感知相对安全的行驶方向。安全场不同方向的安全程度由空间移动平台内部和外部环境因素决定,这些因素共同量化了空间移动平台不同方向的安全程度。安全场由初始安全场和风险场组成,他们叠加组合成的包络面凹凸程度成为判定飞行器周围的安全程度的标准。当空间移动平台某些方向的包络面凹陷时,代表这些方向的安全程度较低,有发生碰撞或者该方向速度过快的风险,应该重点关注,并且尽可能绕过这些区域。设定空间移动平台静止,且监视范围内没有障碍物时,周围的安全场为初始安全场,由于周围任意方向的安全程度是相等的,则初始安全场是以原点为球心的球形包络场,如图1所示。According to the special driving conditions such as obstacle avoidance and safety assessment in the three-dimensional environment where the space mobile platform exists, the present invention proposes a method for establishing the safety field of the space mobile platform based on the artificial potential field. The safety field is an artificial potential energy field used to evaluate the safety degree of different directions within the monitoring range of the surrounding environment when it is still or in space motion. It has the advantages of small amount of calculation, intuition, and real-time update. Human drivers can see obstacles in certain directions earlier and perceive that these directions are less safe than others. After establishing a safe field, the space mobile platform can also perceive relatively safe driving directions. The safety degree of different directions in the safety field is determined by the internal and external environmental factors of the space mobile platform, and these factors together quantify the safety degree of the space mobile platform in different directions. The safety field is composed of the initial safety field and the risk field, and the concavity and convexity of the envelope formed by their superimposition and combination become the standard for judging the safety degree around the aircraft. When the envelope surface of the space mobile platform is concave in some directions, it means that the safety level of these directions is low, there is a risk of collision or the speed in this direction is too fast, you should pay attention to it, and try to bypass these areas as much as possible. When the space mobile platform is stationary and there are no obstacles in the monitoring range, the surrounding safety field is the initial safety field. Since the safety degree in any direction around is equal, the initial safety field is a spherical envelope with the origin as the center of the sphere. field, as shown in Figure 1.
在空间移动平台的飞行过程中,障碍物是最主要的客观环境安全风险影响,因此其构成了安全场模型中的风险场。风险场是搜索监视范围内的所有障碍物,根据障碍物的状态对安全场进行改进。风险场和安全场是相互对立的,空间移动平台周围某一方向的风险场增加,则这一方向的安全场会相应减少,则这一方向的安全程度降低。风险场的大小与很多因素有关,其中最重要的是障碍物相对空间移动平台的距离。对于距离空间移动平台较远的障碍物而言,他们对空间移动平台的安全影响较小。而距离空间移动平台较近的障碍物则视为高风险的障碍物,产生较大的风险场,需要对安全场的包络面有较大影响。During the flight of the space mobile platform, obstacles are the most important objective environmental safety risk impact, so they constitute the risk field in the safety field model. The risk field is to search for all obstacles within the monitoring range, and improve the safety field according to the state of the obstacles. The risk field and the safety field are opposite to each other. If the risk field increases in a certain direction around the space mobile platform, the safety field in this direction will decrease accordingly, and the safety degree in this direction will decrease. The size of the risk field is related to many factors, the most important of which is the distance of the obstacle relative to the space mobile platform. For obstacles that are far away from the space mobile platform, they have less impact on the safety of the space mobile platform. Obstacles that are closer to the space mobile platform are regarded as high-risk obstacles, resulting in a larger risk field, which needs to have a greater impact on the envelope of the safety field.
在风险场的模型构建中,障碍物会对空间移动平台产生相应二维正态分布的风险场,具有对称、中间较高、外侧曲线平滑的特点,适合在球形包络的初始安全场上进行叠加。除相对空间移动平台的距离之外,风险场还应与障碍物的质量mi成正比,根据上述分析,式(1)是风险场的表达式。障碍物产生的风险场与初始安全场叠加后形成最终的安全场,空间移动平台安全场的包络面会产生改变,这表示飞行器不同方向的安全系数发生了改变,如式(2)。In the model construction of the risk field, obstacles will generate a corresponding two-dimensional normal distribution risk field for the space mobile platform, which has the characteristics of symmetry, high middle, and smooth outer curve, and is suitable for the initial safety field of the spherical envelope. overlay. In addition to the distance to the mobile platform in space, the risk field should also be proportional to the massmi of the obstacle. According to the above analysis, Equation (1) is the expression of the risk field. The risk field generated by obstacles is superimposed with the initial safety field to form the final safety field, and the envelope of the safety field of the space mobile platform will change, which means that the safety factor of the aircraft in different directions has changed, as shown in formula (2).
其中,k表示质量系数,θi与表示以Pi为原点的球极坐标系的方位角,i表示第i个障碍物,μ1i,μ2i分别表示θi与的期望,σ1i,σ2i分别表示θi与的均方差,ρ表示θi与的相关系数。Among them, k represents the quality coefficient, θi and Indicates the azimuth angle of the spherical polar coordinate system with Pi as the origin, i indicates the i-th obstacle, μ1i , μ2i respectively indicate θi and The expectation of , σ1i , σ2i represent θi and The mean square error of , ρ means θi and correlation coefficient.
为了解决障碍物动态情况下的空间移动平台安全场模型建立问题,本发明不仅要考虑障碍物的空间位置和质量,还要考虑运动障碍物速度的大小和方向。提出了相对速度法,在公式(1)的基础上进一步改进风险场的函数。在空间移动平台和障碍物都静止或速度缓慢的情况下,可以运用以上的安全场模型进行安全评估分析。但是对于高速运动的空间移动平台而言,空间移动平台和障碍物可能存在很大的相对速度,这会导致安全场对这些障碍物的评估不准确的问题。如果障碍物向空间移动平台的方向高速行驶,会导致空间移动平台不能及时注意这一高风险障碍物。图2,图3分别表示障碍物位置相同,相对空间移动平台速度不同时的安全场模型,其中图3相对飞行器速度较快。In order to solve the problem of building a safe field model of a space mobile platform under dynamic obstacles, the present invention not only considers the spatial position and quality of the obstacle, but also considers the magnitude and direction of the velocity of the moving obstacle. A relative velocity method is proposed to further improve the function of the risk field on the basis of formula (1). In the case that the space mobile platform and obstacles are static or slow, the above safety field model can be used for safety assessment analysis. But for a space mobile platform moving at high speed, there may be a large relative speed between the space mobile platform and obstacles, which will lead to inaccurate evaluation of these obstacles by the safety field. If the obstacle travels at high speed in the direction of the space mobile platform, the space mobile platform cannot pay attention to this high-risk obstacle in time. Fig. 2 and Fig. 3 represent the safety field model when the obstacle position is the same and the speed is different relative to the space mobile platform, among which Fig. 3 is relatively faster than the aircraft.
如果障碍物向空间移动平台相反的速度行驶,则应将这一障碍物对安全场的影响降低。利用空间移动平台与移动障碍物在相对速度上做安全场模型的完善,新的风险场定义如下,式(3)。If the obstacle travels to the opposite speed of the space mobile platform, the impact of this obstacle on the safety field should be reduced. Using the space mobile platform and moving obstacles to complete the safety field model in terms of relative speed, the new risk field is defined as follows, formula (3).
其中,表示第i个障碍物相对空间移动平台的速度,k表示质量系数,θi与表示以Pi为原点的球极坐标系的方位角,i表示第i个障碍物,μ1i,μ2i分别表示θi与的期望,σ1i,σ2i分别表示θi与的均方差,ρ表示θi与的相关系数。in, Indicates the speed of the i-th obstacle relative to the space mobile platform, k indicates the quality coefficient, θi and Indicates the azimuth angle of the spherical polar coordinate system with Pi as the origin, i indicates the i-th obstacle, μ1i , μ2i respectively indicate θi and The expectation of , σ1i , σ2i represent θi and The mean square error of , ρ means θi and correlation coefficient.
本方法可适用于所有空间移动平台,包括飞行器、无人机和飞行汽车等。This method can be applied to all space mobile platforms, including aircraft, drones and flying cars.
最后所应说明的是,以上实施例仅用以说明本发明的技术方案而非限制。尽管参照实施例对本发明进行了详细说明,本领域的普通技术人员应当理解,对本发明的技术方案进行修改或者等同替换,都不脱离本发明技术方案的精神和范围,其均应涵盖在本发明的权利要求范围当中。Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than limit them. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent replacements to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all of them should be included in the scope of the present invention. within the scope of the claims.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117369479B (en)* | 2023-12-04 | 2024-02-13 | 江苏莳光地理信息科技有限公司 | A UAV obstacle early warning method and system based on oblique photogrammetry technology |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2730522A1 (en)* | 2008-07-11 | 2009-01-22 | Acumine Pty Ltd | Method and system for enhancing the safety of a region |
| CN107608346A (en)* | 2017-08-30 | 2018-01-19 | 武汉理工大学 | Ship intelligent barrier avoiding method and system based on Artificial Potential Field |
| CN110208816A (en)* | 2019-06-04 | 2019-09-06 | 浙江海洋大学 | For the automatic differentiating obstacle of marine unmanned boat and recognition methods |
| CN110908373A (en)* | 2019-11-11 | 2020-03-24 | 南京航空航天大学 | An Intelligent Vehicle Trajectory Planning Method Based on Improved Artificial Potential Field |
| CN111204336A (en)* | 2020-01-10 | 2020-05-29 | 清华大学 | Vehicle driving risk assessment method and device |
| CN112904842A (en)* | 2021-01-13 | 2021-06-04 | 中南大学 | Mobile robot path planning and optimizing method based on cost potential field |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2730522A1 (en)* | 2008-07-11 | 2009-01-22 | Acumine Pty Ltd | Method and system for enhancing the safety of a region |
| CN107608346A (en)* | 2017-08-30 | 2018-01-19 | 武汉理工大学 | Ship intelligent barrier avoiding method and system based on Artificial Potential Field |
| CN110208816A (en)* | 2019-06-04 | 2019-09-06 | 浙江海洋大学 | For the automatic differentiating obstacle of marine unmanned boat and recognition methods |
| CN110908373A (en)* | 2019-11-11 | 2020-03-24 | 南京航空航天大学 | An Intelligent Vehicle Trajectory Planning Method Based on Improved Artificial Potential Field |
| CN111204336A (en)* | 2020-01-10 | 2020-05-29 | 清华大学 | Vehicle driving risk assessment method and device |
| CN112904842A (en)* | 2021-01-13 | 2021-06-04 | 中南大学 | Mobile robot path planning and optimizing method based on cost potential field |
| Title |
|---|
| 基于改进人工势场的无人机编队避障控制研究;张佳龙 等;《西安交通大学学报》;20181130;第52卷(第11期);第112-119页* |
| Publication number | Publication date |
|---|---|
| CN113781633A (en) | 2021-12-10 |
| Publication | Publication Date | Title |
|---|---|---|
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