CN111846139A - Comprehensive quantitative assessment method for intelligent navigation performance of unmanned surface vehicle - Google Patents
Comprehensive quantitative assessment method for intelligent navigation performance of unmanned surface vehicle Download PDFInfo
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Abstract
The invention relates to the field of autonomous navigation research and design of unmanned surface vehicles, in particular to an intelligent comprehensive quantitative assessment method for navigation performance of unmanned surface vehicles.
Description
Technical Field
The invention relates to the field of research and design of autonomous navigation of unmanned surface vehicles, in particular to a comprehensive quantitative evaluation method for intelligent navigation performance of unmanned surface vehicles.
Background
The unmanned surface vessel is an unmanned surface vessel with tonnage less than or equal to 500 tons. By additionally arranging different load systems, tasks such as patrol, search and rescue, fire fighting, emergency response, hydrological measurement and the like can be executed in the civil field, and tasks such as reconnaissance, guard, attack, anti-diving, blocking and blocking, electronic reconnaissance and countermeasure can be executed in the military field. At present, aiming at the autonomous sailing performance of the unmanned surface vehicle, the provided index system, assessment means and assessment method are simple, and the autonomous sailing performance of the unmanned surface vehicle platform is difficult to reflect comprehensively.
Disclosure of Invention
The invention aims to solve the problems and provides a comprehensive quantitative evaluation method for intelligent navigation performance of an unmanned surface vehicle, which adopts the following technical scheme:
a comprehensive quantitative assessment method for intelligent navigation performance of unmanned surface vehicle comprises the following steps:
(1) autonomous tracking performance assessment
Setting a navigation path with an inflection point, a starting point and a target point in a test field, measuring the sum of absolute values of rotation angles of an unmanned ship on the navigation path as a track smoothness TSM, determining a capture radius R at the inflection point according to factors such as the volume of the unmanned ship, the flow velocity of a water area and the like, taking a circular range with the inflection point as the center of a circle and the capture radius R as the radius as a path point at the inflection point, and measuring the minimum distance dist between the unmanned ship and the inflection point when the unmanned ship passes through the path pointminComparing the path point deviation degree with the capture radius R and calculating to obtain a path point deviation degree MD;
secondly, recording the sailing time T and the total oil consumption E required by the unmanned boat in the sailing process, wherein the sailing time T is
T＝te-ts(1)
Wherein t issTime for unmanned boat to drive into sailing area, teThe total oil consumption E is the time when the unmanned boat is driven out of the navigation area
E＝Ee-Es(2)
Wherein EsFor the amount of fuel when the unmanned ship is driven into the navigation area, EeThe fuel quantity when the unmanned boat is driven out of the navigation area;
calculating the estimated value IND1 of the autonomous tracking performance of the unmanned ship by using a linear weighted summation method
IND1＝k11×TSM+k12×MD+k13×T+k14×E (3)
k11+k12+k13+k14＝1； (4)
Wherein k is31、k32、k33And k34The weights respectively allocated to the track smoothness TSM, the route point deviation MD, the navigation time T and the total oil consumption E,each weight is determined by an expert;
(2) autonomic awareness performance assessment
Firstly, specifying a navigation water area in a test field, setting an unmanned ship navigation starting point and a barrier static to water in the specified water area, identifying the barrier and reporting to a shore foundation by the unmanned ship through sensor equipment, then returning to the starting point, and determining the minimum safe collision avoidance distance D of the unmanned ship according to the volume, the speed and the external environment of the unmanned shipsafeThe minimum distance dis between the unmanned surface vehicle and the obstacleminDistance D from minimum safe collision avoidancesafeComparing and calculating to obtain the detection risk HBO;
secondly, calculating the induction effect PER of the unmanned ship according to the integrity of the obstacle information acquired by the unmanned ship;
recording the sailing time T and the total oil consumption E required by returning to the starting point after the unmanned ship starts from the starting point to finish the detection task, wherein the calculation formulas are respectively shown as a formula (1) and a formula (2);
fourthly, calculating the evaluation value IND2 of the autonomous perception performance of the unmanned ship by using a linear weighted summation method
IND2＝k21×HBO+k22×PER+k23×T+k24×E (5)
k21+k22+k23+k24＝1； (6)
Wherein k is21、k22、k23And k24Weights respectively allocated to the detection risk HBO, the induction effect PER, the navigation time T and the total oil consumption E, and each weight is determined by an expert;
(3) autonomous voyage performance assessment
Calculating the estimated value TOT of the autonomous navigation performance of the unmanned ship by using a linear weighted summation method
TOT＝k1×IND1+k2×IND2 (7)
k1+k2＝1， (8)
Wherein k is1And k2Weights respectively assigned to the unmanned ship autonomous tracking performance IND1 and the autonomous perception performance IND2 are determined by experts, and the autonomous navigation performance and the evaluation value of the unmanned ship areIn inverse proportion.
On the basis of the scheme, the calculation formula of the track smoothness TSM is as follows
Wherein theta istThe course of the unmanned ship at the time t;
minimum distance dist between unmanned ship and inflection point when unmanned ship passes through path pointminIs calculated by the formula
distmin＝min{||pt-pt'||} (10)
Wherein p istIs the geographic coordinate vector (x) of the unmanned ship at the moment tt,yt)，pt' is the geographical coordinate vector (x) of the waypoint at time tt',yt')；
The single path point deviation degree D is calculated by the formula
The deviation degree MD of the unmanned ship passing through n path points is calculated according to the formula
The detection risk HBO is
The smaller the HBO value is, the smaller the detection risk is;
an expert at a shore-based command center evaluates the information integrity S according to the information acquired by the unmanned ship according to the evaluation basis:
table 1 information integrity evaluation table
| Serial number | Information integrity S evaluation item | Score value |
| 1 | Captured target photograph | 0.5 |
| 2 | Distance to unmanned boat when target is found | 0.1 |
| 3 | Orientation of target to unmanned boat when found | 0.1 |
| 4 | Obstacle target longitude and latitude coordinates | 0.1 |
| 5 | Size of target radius of obstacle | 0.2 |
When one item is finished, accumulating corresponding scores to obtain information integrity S;
then the unmanned boat has the induction effect PER of
PER＝1-S (14)
Based on the above scheme, the above autonomous tracking performance evaluation and autonomous sensing performance evaluation are repeated n times, and the average value of the above parameters, that is, the average value of the above parameters is calculated
Wherein
Is the average of the variables XiThe variable value measured for the ith time; variables X respectively refer to the navigation time T, the total oil consumption E, the track smoothness TSM, the path point deviation MD, the detection danger HBO and the induction effect PER.
Based on the above-mentioned scheme, the obtained average value is normalized, that is
Wherein X*Is a normalized value of a variable XminIs each XiMinimum value of (1), i.e. Xmin＝min{X1,X2,Λ,Xn}，XmaxIs each XiMaximum value of (1), i.e. Xmax＝max{X1,X2,Λ,Xn}；
Finally obtaining the navigation time normalization value T*Normalized value of total oil consumption E*Track smoothness normalization value TSM*Normalized value MD of route point deviation*Detection risk normalization value HBO*And normalized value PER of induction effect*Then the unmanned ship autonomous tracking performance estimated value IND1 and the unmanned ship autonomous perception performance estimated value IND2 are calculated as
IND1＝k11×TSM*+k12×MD*+k13×T*+k14×E*(17)
IND2＝k21×HBO*+k22×PER*+k23×T*+k24×E*(18)
Preferably, the method further comprises the following steps:
selecting a navigation path, a starting point and a target point of an unmanned ship in a test field, calculating a course deviation delta theta between the unmanned ship and a preset course theta according to the direction of the unmanned ship during running, and calculating a course deviation smoothness CDM according to the course deviation delta theta in the navigation process;
secondly, recording the sailing time T and the total oil consumption E required by the unmanned ship in the sailing process, wherein the calculation formulas are respectively shown as a formula (1) and a formula (2);
thirdly, calculating the estimated value IND3 of the unmanned ship heading keeping performance by using a linear weighted summation method
IND3＝k31×CDM+k32×T+k33×E (19)
k31+k32+k33＝1 (20)
Wherein k is31、k32And k33And weights respectively allocated to the heading deviation smoothness CDM, the voyage time T and the total oil consumption E, wherein each weight is determined by an expert.
On the basis of the scheme, the autonomous navigation performance evaluation TOT of the unmanned ship is
TOT'＝k1'×IND1+k2'×IND2+k3×IND3 (21)
k1'+k2'+k3＝1， (22)
Wherein k is1'、k2' and k3Weights respectively assigned to the unmanned ship autonomous tracking performance evaluation value IND1, the autonomous perception performance evaluation value IND2 and the heading keeping performance evaluation value IND3 are determined by experts, and the autonomous navigation performance of the unmanned ship is inversely proportional to the evaluation values.
The invention has the beneficial effects that: according to the scheme, parameters such as the navigation time, the fuel quantity and the navigation path of the unmanned ship are measured and calculated, the autonomous tracking performance, the autonomous perception performance and the course keeping performance of the unmanned ship in the autonomous navigation process are comprehensively evaluated, the navigation performance of the unmanned ship is quantitatively and comprehensively evaluated through weight distribution and normalization calculation, the consideration factors are comprehensive, the evaluation method is scientific and reasonable, and the unmanned ship is suitable for various water test sites such as lakes, rivers and seas.
Drawings
FIG. 1: the path point range schematic diagram at the inflection point of the autonomous tracking performance evaluation path of the unmanned ship;
FIG. 2: the minimum distance schematic diagram of the unmanned ship autonomous tracking performance evaluation;
FIG. 3: an unmanned ship autonomous tracking performance evaluation path tracking test schematic diagram;
FIG. 4: an unmanned ship autonomous perception performance evaluation test schematic diagram;
FIG. 5: unmanned ship course keeps performance test schematic diagram.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
example 1
The assessment of the autonomous navigation performance of the unmanned ship mainly comprises the following three parts
(1) Autonomous tracking performance assessment
As shown in fig. 1 and 2, when the unmanned surface vehicle passes through the inflection point during the autonomous tracking, the unmanned surface vehicle generally does not pass through the inflection point directly, but deviates from the inflection point by a certain distance, so as to continue the tracking by bypassing the inflection point. And setting a capturing radius R for each inflection point during the test, and setting a circle taking the inflection point as a center and the capturing radius R as a radius as a path point at the inflection point, wherein when the unmanned ship enters the path point, namely the value of the unmanned ship from the path point is smaller than the capturing radius, the unmanned ship is considered to successfully pass through the inflection point.
Test scene
As shown in fig. 3, it is assumed that a pair of regular octagonal regions with water being still are arranged in the test site, each side of each regular octagonal region is 0.5km, the unmanned ship in the test is launched from the point a, the regular octagonal track is tracked and navigated at the speed of 15Kn in the counterclockwise direction, and the navigation is finished when the unmanned ship arrives at the point a again.
Performance evaluation calculation
a. Recording the time t of the unmanned ship from the point AsAnd time t at the end of the testeCalculating the navigation time T according to the formula (1);
b. calculating the fuel quantity E of the unmanned boat starting from the point AsAnd the amount of fuel E at the end of the testeCalculating the total fuel quantity E according to the formula (2);
c. continuously acquiring and measuring the sum of absolute values of conversion angles of the unmanned ship on the navigation path in the test, and calculating the track smoothness TSM of the unmanned ship according to the formula (9);
d. continuously measuring and calculating the minimum distance dist of the unmanned ship from the inflection point according to the formulas (10) to (12)minSingle path point deviation degree D and multi-path point deviation degree MD;
e. performing a plurality of tests in the test scene, repeating the steps a to E, respectively calculating and obtaining the voyage time T, the total fuel quantity E, the track smoothness TSM and the multi-path point deviation MD measured and calculated each time according to each voyage result, and calculating the average value of the parameters according to a formula (15);
f. weights are distributed by experts in the field according to the importance of the parameters, and the unmanned ship autonomous tracking performance evaluation value IND1 is obtained through calculation according to the formulas (3) and (4).
(2) Autonomic awareness performance assessment
The autonomous perception performance refers to the performance of detecting an obstacle by the unmanned ship in the sailing process, and if the distance between the unmanned ship and the obstacle is too close to the obstacle when the unmanned ship detects the obstacle in the sailing process, the sailing safety of the unmanned ship can be threatened; if the detection content of the obstacles is not complete, the shore-based command center can not accurately identify the information and the nature of the obstacles. Before evaluation, an expert determines the minimum safe collision avoidance distance D of the unmanned ship according to the factors of the unmanned ship such as volume, speed, external environment and the likesafeThe distance between the unmanned boat and the barrier is less than DsafeThe unmanned ship is considered to be threatened to the navigation safety of the unmanned ship.
Test scene
As shown in fig. 4, a sailing water area is specified in a test site, the water area is a square area with the side length of 3km, a shore-based command center is arranged beside the water area, a sailing starting point of an unmanned ship and an obstacle which is static to water are arranged in the specified water area, the number of the obstacles can be 1 or more, the unmanned ship starts from the specified starting point, and the test is finished when the unmanned ship returns to the starting point after the unmanned ship finishes detecting the specified obstacle in the water area.
The unmanned ship can recognize the target obstacle by adopting sensor equipment such as a camera, a photoelectric sensor, a radar sensor, a laser sensor and the like, and transmits a recognition result to a shore-based command center.
Performance evaluation calculation
a. Recording the time t of the unmanned ship from the point AsAnd time t at the end of the testeCalculating the navigation time T according to the formula (1);
b. calculating the fuel quantity E of the unmanned boat starting from the point AsAnd the amount of fuel E at the end of the testeCalculating the total fuel quantity E according to the formula (2);
c. continuously collecting and storing minimum distance dis between unmanned boat and barrierminThe calculation formula is
dismin＝min{||pt_usv-pt_obs||} (23)
Wherein p ist_usvIs the geographic coordinate vector (x) of the unmanned ship at the moment tt_usv，yt_usv)，pt_obsIs the geographic vector coordinate (x) of the dynamic obstacle at time tt_obs，yt_obs)；
d. Calculating the detection risk HBO according to the calculation result and the formula (13), wherein the smaller the HBO value is, the smaller the detection risk is;
e. the unmanned ship transmits the detected content back to a shore-based command center, evaluates the information integrity S obtained by the unmanned ship according to the evaluation content and the evaluation standard in the table 1, and calculates the unmanned ship induction effect PER according to the formula (14);
f. the information integrity S and the induction effect PER of n obstacles detected by the unmanned ship are averaged to be used as an evaluation parameter of the autonomous sensing performance of the unmanned ship;
g. carrying out a plurality of tests in a test scene, repeating the steps a-f, respectively calculating and obtaining the navigation time T, the total fuel quantity E, the detection danger degree HBO and the induction effect PER which are measured and calculated each time according to the navigation result each time, and calculating the average value of the parameters according to a formula (15);
h. weights are distributed by expert scholars in the field according to the importance of each parameter, and an unmanned ship autonomous collision avoidance performance evaluation value IND2 is obtained through calculation according to a formula (5) and a formula (6).
(3) And (4) calculating to obtain an unmanned ship autonomous navigation performance evaluation value TOT according to the evaluation and calculation results and the formulas (7) and (8), wherein the smaller the value is, the better the autonomous navigation performance of the unmanned ship is.
Example 2
Based on the embodiment 1, the normalized value T of the navigation time is respectively calculated according to the formula (16)*Normalized value of total oil consumption E*Track smoothness normalization value TSM*Normalized value MD of route point deviation*Detection risk normalization value HBO*And normalized value PER of induction effect*Based on the above calculation results, the unmanned ship autonomous tracking performance evaluation value IND1 and the unmanned ship autonomous perception performance evaluation value IND2 are calculated according to equations (17) and (18).
Example 3
On the basis of the embodiment, the comprehensive quantitative assessment method for the intelligent navigation performance of the unmanned surface vehicle further comprises heading maintenance performance assessment:
test scene
As shown in fig. 5, A, B are two points of the test site which are stationary with respect to the ground, the two points are separated by 1km, and in the test process, an unmanned ship (marked as USV) sails from point a to point B at a sailing speed of 15kn, and the test is finished when the unmanned ship reaches point B.
Performance evaluation calculation
a. Setting a heading theta according to the relative position of the point A, B;
b. recording the time t of the unmanned ship from the point AsAnd time t to point BeCalculating the navigation time T according to the formula (1);
c. calculating the fuel quantity E of the unmanned boat starting from the point AsAnd the amount of fuel E at point BeCalculating the total fuel quantity E according to the formula (2);
d. continuously acquiring and storing the actual course of the unmanned ship in the test, and calculating the course deviation smoothness CDM of the unmanned ship:
Δθt＝θt-θ (24)
where Δ θtIs the course deviation at time t, θtThe unmanned ship course is at the time t, and theta is the set course at the time t;
the calculation formula of the course deviation smoothness CDM is
e. Repeatedly navigating between A, B for multiple times, repeating above steps a-d, calculating navigation time T, total fuel quantity E and course deviation smoothness CDM according to navigation result, and calculating average value of above parameters according to formula (15);
f. weights are assigned by experts in the field according to the importance of each parameter, and an unmanned ship heading holding performance evaluation value IND3 is obtained through calculation according to a formula (19) and a formula (20).
On the basis of the above evaluation and calculation, the formulas (7) and (8) are respectively modified into formulas (21) and (22), and expert judges perform weight distribution and weighted calculation on the autonomous tracking performance IND1, the autonomous perception performance IND2 and the autonomous heading maintenance performance evaluation IND3 to finally obtain an unmanned ship autonomous navigation performance evaluation result obtained by comprehensive evaluation of the three aspects of performance, wherein the autonomous navigation performance is in inverse proportion to the evaluation value.
The present invention has been described above by way of example, but the present invention is not limited to the above-described specific embodiments, and any modification or variation made based on the present invention is within the scope of the present invention as claimed.
Claims (6)
1. The comprehensive quantitative assessment method for the intelligent navigation performance of the unmanned surface vehicle is characterized by comprising the following steps of:
(1) autonomous tracking performance assessment
Setting a navigation path with an inflection point, a starting point and a target point in a test field, measuring the sum of absolute values of rotation angles of an unmanned ship on the navigation path as a track smoothness TSM, determining a capture radius R at the inflection point according to factors such as the volume of the unmanned ship, the flow velocity of a water area and the like, taking a circular range with the inflection point as the center of a circle and the capture radius R as the radius as a path point at the inflection point, and measuring the minimum distance dist between the unmanned ship and the inflection point when the unmanned ship passes through the path pointminComparing the path point deviation degree with the capture radius R and calculating to obtain a path point deviation degree MD;
secondly, recording the sailing time T and the total oil consumption E required by the unmanned boat in the sailing process, wherein the sailing time T is
T＝te-ts(1)
Wherein t issTime for unmanned boat to drive into sailing area, teThe time when the unmanned boat is driven out of the navigation area,
the total oil consumption E is
E＝Ee-Es(2)
Wherein EsFor the amount of fuel when the unmanned ship is driven into the navigation area, EeThe fuel quantity when the unmanned boat is driven out of the navigation area;
calculating the estimated value IND1 of the autonomous tracking performance of the unmanned ship by using a linear weighted summation method
IND1＝k11×TSM+k12×MD+k13×T+k14×E (3)
k11+k12+k13+k14＝1； (4)
Wherein k is31、k32、k33And k34Weights respectively allocated to the track smoothness TSM, the route point deviation MD, the navigation time T and the total oil consumption E, and each weight is determined by an expert;
(2) autonomic awareness performance assessment
Firstly, specifying a navigation water area in a test field, setting an unmanned ship navigation starting point and a barrier static to water in the specified water area, identifying the barrier and reporting to a shore foundation by the unmanned ship through sensor equipment, then returning to the starting point, and determining the minimum safe collision avoidance distance D of the unmanned ship according to the volume, the speed and the external environment of the unmanned shipsafeThe minimum distance dis between the unmanned surface vehicle and the obstacleminDistance D from minimum safe collision avoidancesafeComparing and calculating to obtain the detection risk HBO;
secondly, calculating the induction effect PER of the unmanned ship according to the integrity of the obstacle information acquired by the unmanned ship;
recording the sailing time T and the total oil consumption E required by returning to the starting point after the unmanned ship starts from the starting point to finish the detection task, wherein the calculation formulas are respectively shown as a formula (1) and a formula (2);
fourthly, calculating the evaluation value IND2 of the autonomous perception performance of the unmanned ship by using a linear weighted summation method
IND2＝k21×HBO+k22×PER+k23×T+k24×E (5)
k21+k22+k23+k24＝1； (6)
Wherein k is21、k22、k23And k24Weights respectively allocated to the detection risk HBO, the induction effect PER, the navigation time T and the total oil consumption E, and each weight is determined by an expert;
(3) autonomous voyage performance assessment
Calculating the estimated value TOT of the autonomous navigation performance of the unmanned ship by using a linear weighted summation method
TOT＝k1×IND1+k2×IND2 (7)
k1+k2＝1， (8)
Wherein k is1And k2Weights are respectively distributed to the unmanned ship autonomous tracking performance IND1 and the autonomous perception performance IND2, each weight is determined by experts, and the autonomous navigation performance of the unmanned ship is inversely proportional to the magnitude of the evaluation value.
2. The method for comprehensively and quantitatively evaluating the intelligent sailing performance of the unmanned surface vehicle according to claim 1, wherein the calculation formula of the track smoothness TSM is
Wherein theta istThe course of the unmanned ship at the time t;
minimum distance dist between unmanned ship and inflection point when unmanned ship passes through path pointminIs calculated by the formula
distmin＝min{||pt-pt'||} (10)
Wherein p istIs an unmanned boatGeographic coordinate vector (x) at time tt,yt)，pt' is the geographical coordinate vector (x) of the waypoint at time tt',yt')；
The single path point deviation degree D is calculated by the formula
The deviation degree MD of the unmanned ship passing through n path points is calculated according to the formula
The detection risk HBO is
The smaller the HBO value is, the smaller the detection risk is;
an expert at a shore-based command center evaluates the information integrity S according to the information acquired by the unmanned ship according to the evaluation basis:
table 1 information integrity evaluation table
When one item is finished, accumulating corresponding scores to obtain information integrity S;
then the unmanned boat has the induction effect PER of
PER＝1-S (14)。
3. The method as claimed in claim 2, wherein the evaluation of the self-tracking performance and the evaluation of the self-perception performance are repeated n times, and the average value of the parameters is calculated, i.e. the average value of the parameters is calculated
Wherein
Is the average of the variables XiThe variable value measured for the ith time; variables X respectively refer to the voyage time T, the total oil consumption E, the track smoothness TSM and the path pointDeviation MD, detection danger HBO and induction effect PER.
4. The method as claimed in claim 3, wherein the average value is normalized, that is, the average value is evaluated
Wherein X*Is a normalized value of a variable XminIs each XiMinimum value of (1), i.e. Xmin＝min{X1,X2,Λ,Xn}，XmaxIs each XiMaximum value of (1), i.e. Xmax＝max{X1,X2,Λ,Xn}；
Finally obtaining the navigation time normalization value T*Normalized value of total oil consumption E*Track smoothness normalization value TSM*Normalized value MD of route point deviation*Detection risk normalization value HBO*And normalized value PER of induction effect*Then the unmanned ship autonomous tracking performance estimated value IND1 and the unmanned ship autonomous perception performance estimated value IND2 are calculated as
IND1＝k11×TSM*+k12×MD*+k13×T*+k14×E*(17)
IND2＝k21×HBO*+k22×PER*+k23×T*+k24×E*(18)。
5. The comprehensive quantitative assessment method for the intelligent navigation performance of the unmanned surface vehicle as claimed in claim 1, further comprising the following steps of:
selecting a navigation path, a starting point and a target point of an unmanned ship in a test field, calculating a course deviation delta theta between the unmanned ship and a preset course theta according to the direction of the unmanned ship during running, and calculating a course deviation smoothness CDM according to the course deviation delta theta in the navigation process;
secondly, recording the sailing time T and the total oil consumption E required by the unmanned ship in the sailing process, wherein the calculation formulas are respectively shown as a formula (1) and a formula (2);
thirdly, calculating the estimated value IND3 of the unmanned ship heading keeping performance by using a linear weighted summation method
IND3＝k31×CDM+k32×T+k33×E (19)
k31+k32+k33＝1 (20)
Wherein k is31、k32And k33And weights respectively allocated to the heading deviation smoothness CDM, the voyage time T and the total oil consumption E, wherein each weight is determined by an expert.
6. The method for comprehensively and quantitatively evaluating the intelligent sailing performance of the unmanned surface vehicle as claimed in claim 5, wherein the TOT for evaluating the autonomous sailing performance of the unmanned surface vehicle is
TOT'＝k1'×IND1+k2'×IND2+k3×IND3 (21)
k1'+k2'+k3＝1， (22)
Wherein k is1'、k2' and k3Weights respectively assigned to the unmanned ship autonomous tracking performance evaluation value IND1, the autonomous perception performance evaluation value IND2 and the heading keeping performance evaluation value IND3 are determined by experts, and the autonomous navigation performance of the unmanned ship is inversely proportional to the evaluation values.
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| CN113917930A (en) * | 2021-11-11 | 2022-01-11 | 中国船舶重工集团公司第七一九研究所 | Unmanned ship navigation state control method based on sensing data |
| CN114112306A (en) * | 2021-12-09 | 2022-03-01 | 中国船舶科学研究中心 | Underwater unmanned vehicle search and exploration performance evaluation test method |
| CN117608273A (en) * | 2024-01-23 | 2024-02-27 | 北京星网船电科技有限公司 | System reliability control method and device |
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