CN111123901A - Unmanned self-propelled vehicle - Google Patents
Unmanned self-propelled vehicle Download PDFInfo
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Abstract
The invention provides an unmanned self-propelled vehicle which is used for moving in a working area and comprises a whole-area map building module, a local map building module, a whole-area traffic area inward-contracting module and a navigation obstacle avoidance module. The whole-area map building module is used for building a whole-area map which corresponds to the working area and is provided with barrier areas and passing areas. The local map building module is used for building a local map and comparing the local map with a whole area map so as to establish the current position of the unmanned self-propelled vehicle. The whole-area passing area inward-contraction module is used for inward contracting the passing area of the whole-area map to form the whole-area passing area inward-contraction map. The navigation obstacle avoidance module guides the unmanned self-propelled vehicle to contract the map to pass to the target position in the whole passing area.
Description
Technical Field
The invention relates to an unmanned self-propelled vehicle, in particular to an unmanned self-propelled vehicle which converts a whole-area map into a whole-area passing area contracted map.
Background
With the development of Artificial Intelligence (AI) technology, more and more mobile robots or service robots are coming out and are gradually applied to various industries, such as a food delivery robot applied to a restaurant, a service robot applied to a bank, or a baggage robot which has recently begun to be applied to an airport in the united states to help passengers to check baggage, etc.
In addition to the humanoid robot, an Automated Guided Vehicle (AGV), or an unmanned self-propelled Vehicle, a sweeping robot, etc., can also be regarded as a generalized artificial intelligence.
However, the above products related to artificial intelligence have not been developed to a stage of thinking by itself, and the humanoid robot still needs a user to give an instruction to actuate the robot, and some unmanned self-propelled vehicles even need special track guidance, as do the unmanned self-propelled vehicle and the sweeping robot. In addition, the working environment may change at any time, people may pass through, obstacles may be moved, and the like, and if the robot or the unmanned autonomous vehicle cannot have corresponding reactions, the robot or the unmanned autonomous vehicle may be damaged.
Disclosure of Invention
In view of the prior art, the unmanned autonomous vehicle requires a user to give instructions to operate, some of the unmanned autonomous vehicle even requires special track guidance, and the working environment of the unmanned autonomous vehicle is changed at any time, which may cause damage if the unmanned autonomous vehicle fails to have corresponding reactions. The invention mainly aims to provide an unmanned self-propelled vehicle, in particular to an unmanned self-propelled vehicle capable of correcting a working area.
The invention aims to solve the problems of the prior art, and adopts necessary technical means to provide an unmanned self-propelled vehicle which is used for moving in a working area and comprises a whole-area map building module, a local map building module, a whole-area traffic area retraction module and a navigation obstacle avoidance module.
The whole-area map building module is used for scanning the working area when the unmanned self-propelled vehicle moves in the working area so as to build a whole-area map of the working area, and the whole-area map comprises at least one barrier area and at least one traffic area located outside the at least one barrier area.
The local map building module is in communication connection with the whole area map building module and is used for scanning a real-time peripheral area where the unmanned self-propelled vehicle moves in the working area in real time so as to build a local map, and comparing the local map with the whole area map so as to confirm the current position of the unmanned self-propelled vehicle.
The whole-area traffic area retraction module is a communication connection whole-area map building module and comprises a traffic area width computing unit, an retraction amount computing unit and a whole-area traffic area retraction map generating unit. The traffic area width computing unit is used for computing the traffic widths of the at least one traffic area in a plurality of sections of the traffic sections. The inner shrinkage calculation unit calculates a plurality of inner shrinkage widths corresponding to the passing sections according to the section passing widths, wherein the wider the inner shrinkage width is, the larger the inner shrinkage width is. The whole-area passing-area inward-contraction map generation unit modifies the at least one passing area of the whole-area map into at least one inward-contraction passing area according to the inward-contraction widths so as to convert the whole-area map into the whole-area passing-area inward-contraction map.
And the navigation obstacle avoidance module is in communication connection with the whole-area map expansion module and the local map building module and is used for guiding the unmanned self-propelled vehicle to pass in at least one internally-contracted passing area according to the internally-contracted map of the whole-area passing area after the current position and the target position are confirmed.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived by the present invention is a navigation obstacle avoidance module in an unmanned autonomous vehicle, comprising an optimal path planning unit for guiding the unmanned autonomous vehicle to pass through an optimal path in at least one inner contracted passing area, wherein the optimal path is one of a time optimal path and a safety optimal path.
Based on the necessary technical means, the subsidiary technical means derived by the invention is that the unmanned self-propelled vehicle further comprises a speed adjusting module, wherein the speed adjusting module is in communication connection with the whole-area traffic area inward-contracting module and the navigation obstacle avoidance module and generates a plurality of moving speeds corresponding to the inward-contracting width so as to control the unmanned self-propelled vehicle to pass at the moving speed corresponding to the inward-contracting width of at least one inward-contracting traffic area where the unmanned self-propelled vehicle passes.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived from the present invention is a whole area map building module in an unmanned autonomous vehicle, comprising a whole area map scanning unit for scanning a working area.
Based on the necessary technical means, the subsidiary technical means derived from the invention is that the whole area map scanning unit in the unmanned self-propelled vehicle is a laser scanning unit.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived from the present invention is a local map building module in an unmanned autonomous vehicle, comprising a local map scanning unit for scanning a real-time peripheral area in real time.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived from the present invention is that the local map scanning unit in the unmanned self-propelled vehicle is a laser scanning unit.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived by the present invention is a module for establishing a local map in an unmanned autonomous vehicle, comprising a map comparison unit for comparing a plurality of local feature points of the local map with a plurality of global feature points of a global map, so as to determine the current position of the unmanned autonomous vehicle when the local feature points and the global feature points coincide with each other.
Based on the above-mentioned necessary technical means, the subsidiary technical means derived from the present invention is to make each of the retracted widths in the unmanned self-propelled vehicle larger than each of the retracted widths of the unmanned self-propelled vehicle, wherein the retracted amount calculating unit corrects each of the retracted widths to a minimum retracted width, and the minimum retracted width is between one thousandth and one half of the width of the self-propelled vehicle.
Based on the above-mentioned necessary technical means, the present invention is derived from an auxiliary technical means that the unmanned autonomous vehicle further comprises an obstacle height determination unit, wherein the obstacle height determination unit is communicatively connected to the navigation obstacle avoidance module, the whole area map building module and the local map building module, and is configured to acquire an obstacle image of each obstacle of the at least one obstacle area, and analyze an obstacle height of the obstacle according to the obstacle height, and when the obstacle height is lower than a step-over height of the autonomous vehicle, the obstacle is defined as a step-over obstacle, and one of the at least one obstacle area corresponding to the obstacle is defined as an extended passage area.
In view of the above, the unmanned self-propelled vehicle provided by the invention converts the map of the whole area into the map of the whole area which is contracted inwards in the passing area, so as to reduce the probability of collision between the unmanned self-propelled vehicle and the barrier area.
Drawings
Fig. 1 is a block diagram illustrating an unmanned self-propelled vehicle according to a first embodiment of the present invention;
fig. 2 is a map of a whole area showing a working area of the unmanned self-propelled vehicle provided by the first embodiment of the present invention;
fig. 3 is a full-area traffic area retracted map showing a work area of the unmanned self-propelled vehicle provided by the first embodiment of the present invention;
FIG. 4 is a block diagram of an unmanned self-propelled vehicle according to a second embodiment of the present invention;
fig. 5 and 5A are schematic views showing a reduced map of a whole traffic area of a work area of an unmanned autonomous vehicle according to a second embodiment of the present invention.
Description of reference numerals:
1. 1 a: unmanned self-propelled vehicle;
11: a whole area map building module;
111: a whole-area map scanning unit;
12: a local map building module;
121: a local map scanning unit;
122: a map comparison unit;
13: a whole-area passing area retraction module;
131: a traffic region width calculation unit;
132: an inner reduction amount operation unit;
133: a whole-area passing area inside-shrinking map generating unit;
14: a navigation obstacle avoidance module;
141: an optimal path planning unit;
15 a: a rate adjustment module;
16: an obstacle height determination unit;
AP1, AP2, AP 3: a passage section;
AP1 ', AP2 ', AP3 ': a retracted traffic section;
AS: a real-time peripheral region;
AW: a working area;
ML: a local map;
MG: a map of the whole area;
MG': shrinking the map in the whole passing area;
o1, O2, O3, O4, O5, O6, O7: an obstacle region;
o11, O21, O31, O41, O51, O61, O71: an amount of barrier expansion;
o7': expanding a passing area;
PP: a current location;
PT: a target location;
w: the width of the self-propelled vehicle;
w1, W2, W3, W4, W5, W6, W7: a section passing width;
w1 ', W2 ', W3 ', W4 ', W5 ', W6 ', W7 ': the retracted section pass width.
Detailed Description
Referring to fig. 1 to 3, fig. 1 is a block diagram illustrating an unmanned self-propelled vehicle according to a first embodiment of the present invention; fig. 2 is a map of a whole area showing a working area of the unmanned self-propelled vehicle provided by the first embodiment of the present invention; and fig. 3 is a full-area traffic area retraction map showing a work area of the unmanned self-propelled vehicle according to the first embodiment of the present invention. As shown in the figure, an unmanned autonomous vehicle 1 has an autonomous vehicle width W, is located in a work area AW, and includes a whole area map building module 11, a local map building module 12, a whole area traffic area retraction module 13, and a navigation obstacle avoidance module 14.
The global map building module 11 includes a global map scanning unit 111, configured to scan a working area AW when the unmanned autonomous vehicle 1 moves within the working area AW, and build a global map MG according to the working area AW. The map MG includes a plurality of obstacle regions O1, O2, O3, O4, O5, and O6 and a plurality of traffic regions other than obstacle regions O1, O2, O3, O4, O5, and O6.
The whole area map scanning unit 111 in this embodiment is a laser scanning unit, and has a fast scanning speed and a wide scanning coverage, and the distance between the obstacle that reflects the laser and the unmanned self-propelled vehicle 1 can be calculated by calculating the time for emitting the laser and receiving the laser, and if the reflected laser is not received, it indicates that there is no obstacle in the direction. However, the present invention is not limited thereto, and in other embodiments, ultrasonic scanning, Signal Strength Ratio (SSR), or other non-contact distance measurement means may be adopted.
The local map building module 12 is a communication link global map building module 11, and includes a local map scanning unit 121 and a map comparing unit 122. The local map scanning unit 121 is configured to scan an instant surrounding area AS where the unmanned autonomous vehicle 1 is located when the unmanned autonomous vehicle 1 moves in the work area AW, and accordingly, the local map creating module 12 may employ the same manner AS the whole area map creating module 11 to create the local map ML. The map comparing unit 122 is used for comparing the local map ML and the global map MG to determine the current position PP of the unmanned autonomous vehicle 1. More precisely, the map comparing unit 122 determines the current position PP of the unmanned autonomous vehicle 1 by using a plurality of local feature points on the local map ML and a plurality of global feature points on the global map MG, such as the obstacle areas O1 and O2, when the local feature points and the global feature points are matched, but not limited thereto, and the map comparing unit 122 may also adopt technologies such as bluetooth multi-point positioning.
The whole-area traffic region retraction module 13 is in communication connection with the whole-area map creation module 11, and includes a traffic region width calculation unit 131, a retraction amount calculation unit 132, and a whole-area traffic region retraction map generation unit 133. The traffic zone width computing unit 131 calculates a plurality of zone traffic widths W1, W2, W3, W4, W5, W6 and W7 of the traffic zone in the plurality of traffic zones AP1, AP2 and AP 3. The retraction amount calculation unit 132 calculates a plurality of retraction widths corresponding to the pass sections according to the section pass widths W1, W2, W3, W4, W5, W6 and W7, wherein the wider the section pass widths W1, W2, W3, W4, W5, W6 and W7, the larger the retraction width corresponding to the wider the width. In addition, in the embodiment, the total of the retracted widths is 20% of the section passing width, and the retracted widths are respectively retracted 10% from the two ends of the section passing widths W1, W2, W3, W4, W5, W6 and W7. The global passing area contracted map generating unit 133 modifies the passing sections AP1, AP2 and AP3 in the global map MG into contracted passing sections AP1 ', AP 2' and AP3 'according to the contracted width, and the passing areas are also modified into contracted passing areas, so as to convert the global map MG into a global passing area contracted map MG'.
The main purpose of converting the whole area map MG into the whole area traffic area retracted map MG' is to reduce the probability that the unmanned autonomous vehicle 1 collides with at least one of the obstacle areas O1, O2, O3, O4, O5, and O6 due to a delay in determination, scanning, or processing. In brief, if the route planned by the retraction map MG' in the all-zone passing area can be passed by the unmanned autonomous vehicle 1, it means that the unmanned autonomous vehicle 1 can also pass through the all-zone map MG which is not retracted originally, that is, the actual corresponding work area AW. In the original whole-area map MG, the route through which the unmanned autonomous vehicle 1 can almost exactly pass may be converted into the whole-area passing area retracted map MG', and then the retracted route corresponding to the route cannot pass, so that the unmanned autonomous vehicle 1 abandons the retracted route, and even if the unmanned autonomous vehicle 1 in the whole-area map MG can exactly pass through the route, the probability that the unmanned autonomous vehicle 1 collides with the obstacle area can be effectively reduced.
In other words, the whole-area map MG is converted into the whole-area traffic area retracted map MG ', which can also be regarded as a plurality of retracted section traffic widths W1', W2 ', W3', W4 ', W5', W6 'and W7' modified according to the retracted widths W1, W2, W3, W4, W5, W6 and W7, and the retracted section traffic widths W1 ', W2', W3 ', W4', W5 ', W6' and W7 are scaled down by the section traffic widths W1, W2, W3, W4, W5, W6 and W7. In the present embodiment, the retracted section passage widths W1 ', W2', W3 ', W4', W5 ', W6' and W7 are 80% of the section passage widths W1, W2, W3, W4, W5, W6 and W7; similarly, barrier regions O1, O2, O3, O4, O5, and O6 may be considered to generate barrier inflation amounts O11, O21, O31, O41, O51, and O61, respectively.
More specifically, the retracted section passing widths W1 ', W2', W3 ', W4', W5 ', W6' and W7 'are, in order from large to small, W7', W6 ', W4', W3 ', W1', W2 'and W5', wherein the retracted section passing widths W6 ', W4', W3 'and W1' are equal to each other. The global traffic region retraction module 13 may be a chip, a processor, a controller or other components that can be used to calculate the retraction amount, and is installed with relevant retraction calculation software.
The navigation obstacle avoidance module 14 is communicatively connected to the whole-area traffic area retraction module 13 and the local map creation module 12, and is configured to guide the unmanned autonomous vehicle 1 to pass through the retraction sections AP1 ', AP 2', and AP3 'according to the whole-area traffic area retraction map MG' after confirming the current position PP and the target position PT. The navigation obstacle avoidance module 14 may be a controller, a processor or other devices that can be used to navigate obstacle avoidance and that are installed with relevant navigation software or navigate according to relevant route guidance rules.
In the present embodiment, the navigation obstacle avoidance module 14 includes an optimal path planning unit 141, and the optimal path planning unit 141 is used for planning an optimal path for the unmanned autonomous moving vehicle 1 to move from the current position PP to the target position PT. The best path may be a time best path or a safety best path.
The shortest path from the current position PP to the target position PT is defined as the time-optimal path, which is the transit contraction transit section AP 1' in this embodiment. The safe optimal path is defined as the one of the retracted passing sections that restricts the maximum passing width, in this embodiment, the retracted passing section AP 3'. The restricted passage width is the narrowest point of the retracted section in the retracted passage section, the restricted passage width of the retracted passage section AP1 'is the retracted section passage width W2', the restricted passage width of the retracted passage section AP2 'is the retracted section passage width W5', and the restricted passage width of the retracted passage section AP3 'is the retracted section passage width W6'. Since the largest one of the retracted section passing widths is the retracted section passing width W6 ', the safe optimal path is defined as passing through the retracted section AP 3'. The safety is defined herein as that the probability of collision between the unmanned autonomous vehicle 1 and the obstacle is the lowest, because the retracted section passing width W6 'is greater than the retracted section passing widths W2' and W5 ', which means that the retracted passing section AP 3' is the widest, and the retracted passing area AP3 'corresponds to the full-area map MG and the width is enlarged and reduced again, the probability of collision between the passing section AP3 of the unmanned autonomous vehicle 1 corresponding to the retracted passing section AP 3' and the obstacle in the actual working area AW is the lowest.
In addition, since the retracted passing section AP2 ' has a retracted section passing width W5 ' smaller than the self-propelled vehicle width W, the navigation obstacle avoidance module 14 does not guide the unmanned self-propelled vehicle 1 to pass through the retracted passing section AP2 '.
In this embodiment, the retraction amount calculating unit 132 calculates a plurality of retraction widths, and when the retraction width is greater than or equal to the width W of the self-propelled vehicle, it indicates that the passing section corresponding to the retraction width is extremely large in the passing width of the section thereof, and if the retraction width is modified according to the retraction width, the retraction map MG' in the full-area passing area is distorted, and the path planning for guiding the unmanned self-propelled vehicle 1 is also affected. Therefore, when the above situation occurs, the retraction amount calculation unit 132 shortens any retraction width equal to or larger than the self-propelled vehicle width W into the minimum retraction width uniformly, and the minimum retraction width is usually between one thousandth and one half times of the self-propelled vehicle width, as shown in fig. 3, the obstacle expansion amounts on the left and right sides of the obstacle regions O3, O4, O5, and O6. In other embodiments of the present invention, the shrinkage amount calculating unit 132 may be configured with the navigation obstacle avoidance module 14 to calculate the shrinkage width, when the passing area is not in the path planned by the navigation obstacle avoidance module 14, the shrinkage amount calculating unit 132 unifies the shrinkage width of the passing area into the minimum shrinkage width, and the minimum shrinkage width is one thousandth of the width of the self-propelled vehicle, i.e., is close to the width without shrinkage, and the shrinkage width is calculated selectively by phase change, which not only can avoid distortion of the map within the passing area of the whole area, but also can directly convert the shrinkage width into the minimum shrinkage width by the shrinkage amount calculating unit 132, and the shrinkage width is not required to be calculated, thereby increasing the calculating efficiency.
Next, please refer to fig. 4 to 5A, wherein fig. 4 is a block diagram of an unmanned self-propelled vehicle according to a second embodiment of the present invention; fig. 5 and 5A are schematic views showing a full-area traffic area retraction map of a work area of an unmanned autonomous vehicle according to a second embodiment of the present invention. As shown, an unmanned autonomous vehicle 1a is substantially the same as the unmanned autonomous vehicle 1 of the first embodiment, except that the unmanned autonomous vehicle 1a further includes a speed adjustment module 15 a.
As in the process of ordinary driving, different driving speeds are available according to different road conditions, when the vehicle is driven on a road with a narrow road width, the driving speed is generally reduced, and when the vehicle is driven on a road with a wide road width, the driving speed can be generally higher.
The speed adjusting module 15a adjusts the moving speed of the unmanned autonomous vehicle 1a according to the shrinking width of the shrinking section where the unmanned autonomous vehicle 1a passes, where the larger the shrinking width is, the larger the section passing width corresponding to the map MG is, so that the larger the shrinking width is, the faster the speed adjusting module 15a generates the corresponding moving speed, and the smaller the shrinking width is, the larger the speed adjusting module 15a generates the corresponding moving speed.
As shown in fig. 5, when the unmanned self-propelled vehicle 1a passes through the retracted section AP1 ', the retracted section AP1 ' has retracted section passing widths W1 ', W2 ' and W3 ', wherein the retracted section passing widths W1 ' and W3 ' are equal to each other and are greater than the retracted section passing width W2 ', and therefore the retracted widths corresponding to the retracted section passing widths W1 ' and W3 ' are also greater than the retracted width corresponding to the retracted section passing width W2 '. Therefore, the moving speed of the unmanned autonomous vehicle 1a passing the retracted section passing widths W1 ' and W3 ' is greater than the moving speed of the retracted section passing width W2 '. Similarly, the moving speed of the unmanned self-propelled vehicle 1a passing through the retracted section passing width W7 'is greater than the moving speed of the unmanned self-propelled vehicle 1a passing through the retracted section passing width W6'. The time from the current position PP to the target position PT can be obtained by matching the moving speed, and the time optimal path with the shortest time can be selected.
The slower the moving speed of the unmanned autonomous vehicle 1a in the retracted passage section where the passage width is narrower, the error caused by the scanning time of the scanned map or the calculation time of calculating the retracted width can be avoided, and the probability of collision between the unmanned autonomous vehicle 1a and the obstacle area can be further reduced.
Preferably, the unmanned autonomous vehicle 1a further includes an obstacle height determining unit 16, and the obstacle height determining unit 16 is configured to obtain an obstacle image of an obstacle in each obstacle region, and analyze the obstacle height of the obstacle according to the obstacle image. When the obstacle height determination unit 16 analyzes that the obstacle height is lower than the self-propelled vehicle stridable height of the unmanned self-propelled vehicle 1a, it indicates that the unmanned self-propelled vehicle 1a can climb over the obstacle. Therefore, the obstacle height determination unit 16 defines the obstacle as a stridable obstacle, and defines an obstacle region corresponding to the obstacle as an extended passage region. The self-propelled vehicle capable of crossing is a height which represents that the unmanned self-propelled vehicle 1a can safely run and cross and does not cause damage to the unmanned self-propelled vehicle 1a, and can be half, one third, one fourth and the like of the whole height of the unmanned self-propelled vehicle 1 a.
The method for analyzing the height of the obstacle by the obstacle height determining unit 16 may utilize laser scanning ranging and image, and coordinate with the calculation of the angle and the trigonometric function, so as to analyze the height of the obstacle, but not limited thereto. In other embodiments of the present invention, the height of the obstacle can also be resolved by using a built-in scale.
The obstacle height determination unit 16 is in communication connection with the navigation obstacle avoidance module 14, the whole area map building module 11, and the local map building module 12. When the obstacle height determination unit 16 determines that the obstacle height of the obstacle is lower than the crossing height of the autonomous moving vehicle, it may send a signal to the navigation obstacle avoidance module 14, the whole-region map building module 11, and the local map building module 12 at the same time, so that the whole-region map building module 11 and the local map building module 12 bring the extended passage area into the whole-region map and the local map, and the navigation obstacle avoidance module 14 guides the unmanned autonomous moving vehicle 1a to pass in the retracted passage section or the extended passage area.
The obstacle height determining unit 16 may also only send a signal to the navigation obstacle avoidance module 14, so that the navigation obstacle avoidance module 14 immediately changes the guidance path, and the unmanned autonomous vehicle 1a passes through the expanded passing area. In addition, the obstacle height determining unit 16 may only send a signal to the global map building module 11 and the local map building module 12, so as to incorporate the extended traffic area into the global map and the local map, and the global traffic area contracting module 13 converts the global map incorporated into the extended traffic area into a new global traffic area contracting map. Finally, the navigation obstacle avoidance module 14 guides the unmanned self-propelled vehicle 1a to pass according to the new contracted map in the whole passing area.
As shown in fig. 5 and 5A, in fig. 5, the obstacle region O7 has generated the obstacle inflation amount O71, and therefore the route of the unmanned self-propelled vehicle 1a bypasses the obstacle region O7 and the obstacle inflation amount O71. In fig. 5A, the image acquiring unit 16 acquires and analyzes the obstacle height of an obstacle (located in the obstacle region O7 but not shown) in the obstacle region O7, and when it is determined that the obstacle height is lower than the self-propelled step-able height, the obstacle is defined as a step-able obstacle, and the obstacle region O7 is defined as an extended passage region O7'. Therefore, the navigation obstacle avoidance module 14 guides the unmanned autonomous vehicle 1a to travel through the expanded passing area O7', so as to shorten the travel path of the unmanned autonomous vehicle 1a, and also enable the unmanned autonomous vehicle 1a to travel straight as much as possible, thereby avoiding the probability of collision of the unmanned autonomous vehicle 1a due to excessive turning.
In summary, compared with the prior art, the unmanned self-propelled vehicle provided by the invention converts the whole-area map into the whole-area inward-contraction map through the whole-area traffic area inward-contraction module, so that the unmanned self-propelled vehicle passes through the inward-contraction traffic section of at least one inward-contraction traffic area of the whole-area inward-contraction map, and the probability of collision between the unmanned self-propelled vehicle and the obstacle is reduced. Preferably, the speed adjusting module can be further used to control the unmanned self-propelled vehicle to pass at different moving speeds according to different retracted widths, so as to further reduce the probability of collision between the unmanned self-propelled vehicle and the barrier.
The above detailed description of the preferred embodiments is intended to more clearly illustrate the features and spirit of the present invention, and is not intended to limit the scope of the present invention by the preferred embodiments disclosed above. On the contrary, it is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
Claims (10)
1. An unmanned self-propelled vehicle for moving within a work area, comprising:
the whole area map building module is used for scanning the working area when the unmanned self-propelled vehicle moves in the working area so as to build a whole area map of the working area, and the whole area map comprises at least one obstacle area and at least one passing area positioned outside the at least one obstacle area;
the local map building module is in communication connection with the whole area map building module and is used for scanning a real-time peripheral area where the unmanned self-propelled vehicle moves in the working area in real time so as to build a local map, and comparing the local map with the whole area map so as to confirm the current position of the unmanned self-propelled vehicle;
the whole-area passing area retraction module is in communication connection with the whole-area map building module and comprises:
a traffic area width calculation unit for calculating the traffic width of the at least one traffic area in a plurality of sections of the traffic section;
the inner shrinkage calculation unit calculates a plurality of inner shrinkage widths corresponding to the plurality of passing sections according to the plurality of section passing widths, wherein the wider the width is, the larger the inner shrinkage width is corresponding to the wider the width is in the plurality of section passing widths; and
a whole-area passing-area contracted map generating unit, which modifies the at least one passing area of the whole-area map into at least one contracted passing area according to the plurality of contracted widths so as to convert the whole-area map into a whole-area passing-area contracted map; and
and the navigation obstacle avoidance module is in communication connection with the whole-area passing area retraction module and the local map building module and is used for guiding the unmanned self-propelled vehicle to pass in the at least one retracted passing area according to the whole-area passing area retraction map after the current position and the target position are confirmed.
2. The unmanned autonomous vehicle of claim 1, wherein the navigation obstacle avoidance module comprises an optimal path planning unit to guide optimal path traffic of the unmanned autonomous vehicle in the at least one retracted traffic area, and the optimal path is one of a time optimal path and a safe optimal path.
3. The unmanned autonomous vehicle of claim 1, further comprising a speed adjustment module communicatively coupled to the all-zone traffic zone retraction module and the navigation obstacle avoidance module, and generating a plurality of moving speeds corresponding to the plurality of retraction widths, so as to control the unmanned autonomous vehicle to travel at the moving speed corresponding to the retraction width of the at least one retraction traffic zone.
4. The unmanned self-propelled vehicle of claim 1, wherein the global area map building module includes a global area map scanning unit and the global area map scanning unit is to scan the work area.
5. The unmanned self-propelled vehicle of claim 4, wherein the global area map scanning unit is a laser scanning unit.
6. The unmanned self-propelled vehicle of claim 1, wherein the local map creation module includes a local map scanning unit and the local map scanning unit is configured to instantaneously scan the immediate surrounding area.
7. The unmanned self-propelled vehicle of claim 6, wherein the local map scanning unit is a laser scanning unit.
8. The unmanned self-propelled vehicle of claim 1, wherein the local map building module comprises a map comparison unit configured to compare a plurality of local feature points of the local map with a plurality of global feature points of the global map, so as to determine the current location of the unmanned self-propelled vehicle when the plurality of local feature points and the plurality of global feature points match.
9. The unmanned self-propelled vehicle of claim 1, wherein each of the plurality of retracted widths that is greater than a self-propelled vehicle width of the unmanned self-propelled vehicle is corrected by the retraction amount calculation unit to a minimum retracted width that is between one thousandth and one half of the self-propelled vehicle width.
10. The unmanned autonomous vehicle of claim 1, further comprising an obstacle height determining unit, communicatively connected to the navigation obstacle avoidance module, the whole area map building module and the local map building module, for obtaining an obstacle image of each obstacle of the at least one obstacle area, so as to analyze an obstacle height of the obstacle, and when it is determined that the obstacle height is lower than a traversable height of the autonomous vehicle, defining the obstacle as a traversable obstacle, and defining one of the at least one obstacle area corresponding to the obstacle as an extended passage area.
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