JP2017097000A - Local map creation device and local map creation method - Google Patents
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本発明は、局所地図作成装置および局所地図作成方法に関し、とくにレーザレンジファインダ（ＬＲＦ）を用いて周辺環境を計測しながら動作するロボットについて、その周辺環境の地図作成を行う局所地図作成装置および局所地図作成方法に関する。 The present invention relates to a local map creation device and a local map creation method, and more particularly to a local map creation device and a local map creation device for creating a map of the surrounding environment of a robot that operates while measuring the surrounding environment using a laser range finder (LRF). It relates to a map creation method.
従来、ロボット等の周辺環境を、レーザレンジファインダ（ＬＲＦ）を用いて距離計測して局所地図を生成し、その局所地図を用いて全体の大域地図を生成するものが公知となっている（例えば、下記特許文献１〜９および非特許文献１等参照）。
このうち、局所地図を作る方法については下記非特許文献１に開示された方法が知られている。
2. Description of the Related Art Conventionally, it is known that a surrounding map of a robot or the like generates a local map by measuring a distance using a laser range finder (LRF), and generates an entire global map using the local map (for example, , See the following Patent Documents 1 to 9 and Non-Patent Document 1).
Among these, the method disclosed in Non-Patent Document 1 below is known as a method for creating a local map.
図１に示すように、レーザレンジファインダ１１は、水平面に一定角度Δθの間隔（角度分解能：例えばΔθ＝１度やΔθ＝０．２５度など）でレーザー光１１ａを照射し、その反射光を検出して障害物２ａや壁２ｂなどの物体（以下、総称する場合は物体２と称する）までの距離を計測している。レーザレンジファインダ１１を搭載し、その距離データを利用して周辺環境を理解して移動するロボット１では、この距離データを地図化する必要がある。 As shown in FIG. 1, the laser range finder 11 irradiates a laser beam 11a on a horizontal plane at intervals of a constant angle Δθ (angle resolution: for example, Δθ = 1 degree, Δθ = 0.25 degree, etc.), and reflects the reflected light. The distance to an object such as the obstacle 2a or the wall 2b (hereinafter collectively referred to as the object 2) is measured. The robot 1 equipped with the laser range finder 11 and using the distance data to understand the surrounding environment and move must map this distance data.
非特許文献１では、図８（ａ）に示すようにレーザレンジファインダ１１などの距離センサによって得られる距離データｒを基に物体２までの距離を取得し、図８（ｂ）に示すように物体２があるところを「１．０」、物体２がない自由空間を「０．０」、未観測または不明を中間の「０．５」の確率で表し、これをグリッド状の確率的障害物地図に変換している。ここでレーザレンジファインダ１１から照射される各レーザー光１１ａには間隔があり連続的ではない。そのため角度分解能をΔθとするとき、そのΔθ分の隙間を埋める必要があり、図８（ｃ）に示すように、一つの距離データｒに対して扇形の領域Ｅで、物体２の有無を表している。なお、図８（ｃ）に示すＦは、未観測領域を示している。 In Non-Patent Document 1, the distance to the object 2 is acquired based on the distance data r obtained by a distance sensor such as the laser range finder 11 as shown in FIG. 8A, and as shown in FIG. The place where the object 2 is present is represented by “1.0”, the free space where the object 2 is absent is represented by “0.0”, and the unobserved or unknown is represented by an intermediate probability of “0.5”. It has been converted to a physical map. Here, the laser beams 11a irradiated from the laser range finder 11 are spaced and are not continuous. Therefore, when the angle resolution is Δθ, it is necessary to fill a gap corresponding to Δθ. As shown in FIG. 8C, the presence or absence of the object 2 is represented by a sector area E with respect to one distance data r. ing. In addition, F shown in FIG.8 (c) has shown the unobserved area | region.
この扇形の領域Ｅを図９に示すようにグリッド状の地図に障害物の確率分布として当てはめ、グリッド状の地図４を作成する。なお、図９に示す例では、未観測または不明の部分をグレーの領域Ａ、障害物がない部分を黒の領域Ｂ、障害物がある部分を白の領域Ｃで示している。
これをすべての方向の距離データに適用し、確率的障害物地図を作成する。これが周辺環境の「局所地図」となる。
As shown in FIG. 9, the fan-shaped region E is applied as a probability distribution of obstacles to a grid-like map to create a grid-like map 4. In the example shown in FIG. 9, an unobserved or unknown part is indicated by a gray area A, a part without an obstacle is indicated by a black area B, and a part with an obstacle is indicated by a white area C.
This is applied to the distance data in all directions to create a probabilistic obstacle map. This is the “local map” of the surrounding environment.
また、ロボット１が走行する範囲全体の地図である「大域地図」は、上記の局所地図をつなぎ合せて作成する。
このつなぎ合わせでは、複数の局所地図を、それぞれロボット１の移動した量だけずらして重ね合わせることになるが、このロボット１の移動量に誤差が含まれる場合、精度のよい大域地図が生成できない。
A “global map” that is a map of the entire range in which the robot 1 travels is created by connecting the local maps.
In this joining, a plurality of local maps are shifted and overlapped by the amount of movement of the robot 1, respectively. However, if the movement amount of the robot 1 includes an error, an accurate global map cannot be generated.
従来、パーティクルフィルタを用いた方法では、各パーティクルに位置・姿勢、大域地図の情報をそれぞれ持たせ、パーティクル毎にロボット１の移動・姿勢変化量（オドメトリからの推定量など）に加え、ランダムなノイズと局所地図を与えて、大域地図と局所地図のマッチングを行う。このマッチングでは、下式(1)により間違いの割合ｄを計算する。 Conventionally, in the method using a particle filter, each particle has information on position / posture and global map, and in addition to the movement / posture change amount of the robot 1 for each particle (estimated amount from odometry, etc.) Given noise and local map, matching global map and local map. In this matching, the error rate d is calculated by the following equation (1).
そして、上記間違いの割合の値ｄからパーティクル毎の尤度ｌpに対して、下式(2)として尤度を更新する。 Then, the likelihood is updated as the following equation (2) with respect to the likelihood l p for each particle from the error ratio value d.
この尤度の値の大きいパーティクルが最も良い大域地図と位置姿勢を保持しているということになる。 This means that particles with a large likelihood value hold the best global map and position and orientation.
しかしながら、非特許文献１の方法では、図１０に示すように壁２ｂに対してレーザレンジファインダ１１で距離を計測した場合、壁２ｂに対するレーザー光１１ａの角度Θが浅くなるにつれ隣り合う障害物計測点Ｐの間隔が空いてしまい、図１１に破線で囲んで示すように実際には壁２ｂがあるのにもかかわらず「物体なし」となる部分が多くなるほか、図１１に一点鎖線で囲んで示すように、本来障害物２ｂがない部分に障害物があるという結果になるなど、実際の周辺環境と異なる部分がでてきてしまう。 However, in the method of Non-Patent Document 1, when the distance is measured with the laser range finder 11 with respect to the wall 2b as shown in FIG. 10, the adjacent obstacle measurement is performed as the angle Θ of the laser beam 11a with respect to the wall 2b becomes shallower. In addition to the fact that the space between the points P becomes empty and there are actually “no objects” despite the fact that there is a wall 2b as shown in FIG. 11 surrounded by a broken line, it is surrounded by an alternate long and short dash line in FIG. As shown in FIG. 4, a part different from the actual surrounding environment appears, such as a result that there is an obstacle in a part where the obstacle 2b is not originally present.
このような地図を重ね合わせて大域地図を構成しようとしても精度良く構築できないことがある。これは、以下の点により上式(1)で得られる間違いの割合ｄの値が正しく得られなくなるためである。
１．本来障害物がない部分が「物体あり」となった局所地図が、過去に大域地図に反映されてしまったこと
２．計測点が飛び飛びとなる部分のため、計測点間が「物体なし」となる部分が多くなること
Even if an attempt is made to construct a global map by superimposing such maps, it may not be constructed with high accuracy. This is because the value of the error rate d obtained by the above equation (1) cannot be obtained correctly due to the following points.
1. 1. The local map where the part that originally has no obstacle is “object present” has been reflected in the global map in the past. Because the measurement points are skipped, there are many parts where there is no object between the measurement points.
このようなことから本発明は、レーザレンジファインダのレーザー光の障害物に対する照射角度によらず、「物体なし」の領域及び「物体あり」の領域を高精度に描画し、大域地図を高精度に生成することができる局所地図作成装置および局所地図作成方法を提供することを目的とする。 For this reason, the present invention draws the "no object" area and the "with object" area with high accuracy, regardless of the irradiation angle of the laser beam to the obstacle of the laser range finder, and the global map with high accuracy. It is an object of the present invention to provide a local map creation device and a local map creation method that can be generated.
上記の課題を解決するための第１の発明に係る局所地図作成装置は、
一定角度間隔で放射状に距離を計測する距離センサから距離データを入力する距離データ入力部と、
前記距離データに基づいて隣り合う二つの計測点間の距離を計算する二点間距離計算部と、
前記二つの計測点間の距離に基づいて隣り合う二つの計測点間に物体が存在する確率を計算する二点間確率計算部と、
前記距離データに基づいて物体の存在が不明な領域を予め設定した「不明領域」に対応する輝度で描画し、前記距離センサから前記計測点までの間を予め設定した「物体なし領域」に対応する輝度で描画する一方、隣り合う二つの計測点間を「物体あり領域」として前記確率に基づく値に応じた輝度で描画してグリッド状の局所地図を生成する局所地図生成部と
を備えることを特徴とする。
The local map creation device according to the first invention for solving the above-described problems is
A distance data input unit for inputting distance data from a distance sensor that measures the distance radially at a constant angular interval;
A point-to-point distance calculation unit that calculates a distance between two adjacent measurement points based on the distance data;
A point-to-point probability calculation unit that calculates the probability that an object exists between two adjacent measurement points based on the distance between the two measurement points;
An area in which the presence of an object is unknown based on the distance data is drawn with a luminance corresponding to a preset “unknown area”, and a distance from the distance sensor to the measurement point is set in advance to correspond to a preset “no object area” A local map generation unit that generates a grid-like local map by drawing at a luminance according to a value based on the probability as a region between two adjacent measurement points as an “object-containing region” It is characterized by.
上記の課題を解決するための第２の発明に係る局所地図作成装置は、
前記局所地図生成部が、前記確率に基づき、隣り合う二つの前記計測点間の距離が短いほど前記「物体あり領域」に近い輝度で隣り合う二つの計測点間を描画し、当該二点間の距離が長いほど前記「不明領域」に近い輝度で隣り合う二つの計測点間を描画する
ことを特徴とする。
A local map creating apparatus according to the second invention for solving the above-mentioned problems is
Based on the probability, the local map generation unit draws between two measurement points adjacent to each other with a luminance close to the “region with object” as the distance between the two measurement points adjacent to each other is shorter. The longer the distance is, the more adjacent the measurement points are drawn with the brightness close to the “unknown area”.
上記の課題を解決するための第３の発明に係る局所地図作成方法は、
一定角度間隔で放射状に距離を計測する距離センサから距離データを入力する第一の工程と、
前記距離データに基づいて隣り合う二つの計測点間の距離を計算する第二の工程と、
前記二つの計測点間の距離に基づいて隣り合う二つの計測点間に物体が存在する確率を計算する第三の工程と、
前記距離データに基づいて物体の存在が不明な領域を予め設定した「不明領域」に対応する輝度で描画し、前記距離センサから前記計測点までの間を予め設定した「物体なし領域」に対応する輝度で描画する一方、隣り合う二つの計測点間を「物体あり領域」として前記確率に基づく値に応じた輝度で描画してグリッド状の局所地図を生成する第四の工程と
を備えることを特徴とする。
A local map creation method according to a third invention for solving the above-described problem is as follows.
A first step of inputting distance data from a distance sensor that measures distances radially at constant angular intervals;
A second step of calculating a distance between two adjacent measurement points based on the distance data;
A third step of calculating a probability that an object exists between two adjacent measurement points based on a distance between the two measurement points;
An area in which the presence of an object is unknown based on the distance data is drawn with a luminance corresponding to a preset “unknown area”, and a distance from the distance sensor to the measurement point is set in advance to correspond to a preset “no object area” And a fourth step of generating a grid-like local map by drawing with a luminance according to the value based on the probability as a region between two adjacent measurement points as an “object-containing region”. It is characterized by.
上記の課題を解決するための第４の発明に係る局所地図作成方法は、
前記第四の工程では、前記確率に基づき、当該二点間の距離が短いほど前記「物体あり領域」に近い輝度で隣り合う二つの計測点間を描画し、当該二点間の距離が長いほど前記「不明領域」に近い輝度で隣り合う二つの計測点間を描画する
ことを特徴とする。
A local map creation method according to a fourth invention for solving the above-described problem is as follows.
In the fourth step, based on the probability, the shorter the distance between the two points is, the lower the distance between the two measurement points is drawn with the brightness close to the “object-containing region”. It is characterized by drawing between two adjacent measurement points with a brightness close to the “unknown area”.
本発明によれば、レーザレンジファインダのレーザー光の障害物に対する照射角度によらず、「物体なし」の領域及び「物体あり」の領域を高精度に描画し、大域地図を高精度に生成することができる。 According to the present invention, the “no object” region and the “object present” region are drawn with high accuracy and the global map is generated with high accuracy, regardless of the irradiation angle of the laser beam to the obstacle of the laser range finder. be able to.
以下、図面を参照しつつ本発明に係る局所地図作成装置および局所地図作成方法について説明する。 Hereinafter, a local map creation device and a local map creation method according to the present invention will be described with reference to the drawings.
図１から図７を用いて本発明の一実施例に係る局所地図作成装置および局所地図作成方法の詳細を説明する。 The details of the local map creation device and local map creation method according to an embodiment of the present invention will be described with reference to FIGS.
図１に示すように、本実施例に係る局所地図作成装置１２は、距離センサとしてのレーザレンジファインダ（LRF）１１を用いて周辺環境を計測しながら動作するロボット１に搭載され、レーザレンジファインダ１１により取得した距離データを用いてロボット１の周辺環境の地図作成を行うものである。 As shown in FIG. 1, a local map creating apparatus 12 according to the present embodiment is mounted on a robot 1 that operates while measuring a surrounding environment using a laser range finder (LRF) 11 as a distance sensor, and is a laser range finder. 11 is used to create a map of the surrounding environment of the robot 1 using the distance data acquired in step 11.
レーザレンジファインダ１１は、水平面に一定角度Δθの間隔（角度分解能：例えばΔθ＝１度やΔθ＝０．２５度など）でレーザー光１１ａを照射し、このレーザー光１１ａの障害物２ａや壁２ｂ等（物体２）による反射光を検出して物体２までの距離を計測する。なお、図１中に示す点Ｐはレーザレンジファインダ１１のレーザー光１１ａによる障害物計測点である。 The laser range finder 11 irradiates the horizontal plane with laser light 11a at intervals of a constant angle Δθ (angular resolution: for example, Δθ = 1 degree, Δθ = 0.25 degree, etc.), and the obstacle 2a and the wall 2b of the laser light 11a. Etc. (object 2) is detected and the distance to the object 2 is measured. A point P shown in FIG. 1 is an obstacle measurement point by the laser beam 11a of the laser range finder 11.
局所地図作成部１２は、図２に示すように、ＬＲＦデータ入力部１２ａ、二点間距離計算部１２ｂ、二点間確率計算部１２ｃ、局所地図生成部１２ｄ、および記憶部１２ｅを備えている。 As shown in FIG. 2, the local map creation unit 12 includes an LRF data input unit 12a, a point-to-point distance calculation unit 12b, a point-to-point probability calculation unit 12c, a local map generation unit 12d, and a storage unit 12e. .
ＬＲＦデータ入力部１２ａは、レーザレンジファインダ１１から距離データを入力し、記憶部１２ｅに保管する。
二点間距離計算部１２ｂは、記憶部１２ｅから読み出した距離データの隣り合う二点間の距離を計算し、結果を記憶部１２ｅに保管する。
二点間確率計算部１２ｃは、記憶部１２ｅから読み出した二点間距離を基に、その二点間の「物体あり」の確率を計算する。求めた確率は、二点間確率として記憶部１２ｅに保管する。
The LRF data input unit 12a receives distance data from the laser range finder 11 and stores it in the storage unit 12e.
The point-to-point distance calculation unit 12b calculates the distance between two adjacent points in the distance data read from the storage unit 12e, and stores the result in the storage unit 12e.
The point-to-point probability calculation unit 12c calculates the probability of “there is an object” between the two points based on the distance between the two points read from the storage unit 12e. The obtained probability is stored in the storage unit 12e as a point-to-point probability.
局所地図生成部１２ｄは、距離データと二点間確率を基に、グリッド状の局所地図データを生成する部分であり、「物体なし」領域描画部１２ｄａと、「物体あり」直線描画部１２ｄｂとを備えている。「物体なし」領域描画部１２ｄａは、初期化されたグリッド状の局所地図データに対し、「物体なし」領域を描画する。「物体あり」直線描画部１２ｄｂは、グリッド状の局所地図データに対し、距離データと二点間確率を用いて、「物体あり」を示す直線を二点間確率の値に応じた輝度で描画する。生成された局所地図は記憶部１２ｅに保管する。
記憶部１２ｅは、距離データ、二点間距離、二点間確率、局所地図等を保管する。
The local map generation unit 12d is a part that generates grid-like local map data based on the distance data and the probability between two points. The “no object” region drawing unit 12da, the “with object” straight line drawing unit 12db, It has. The “no object” area drawing unit 12da draws the “no object” area on the initialized grid-like local map data. The “with object” straight line drawing unit 12db draws a straight line indicating “with object” with brightness corresponding to the value of the point-to-point probability using the distance data and the probability between two points for the grid-like local map data. To do. The generated local map is stored in the storage unit 12e.
The storage unit 12e stores distance data, a distance between two points, a probability between two points, a local map, and the like.
次に、図３を用いて局所地図作成部１２による局所地図作成の流れを説明する。
図３に示すように、局所地図作成部１２では、まず、ＬＲＦデータ入力部１２ａによりレーザレンジファインダ１１から当該レーザレンジファインダ１１によって取得した距離データを入力する（ステップＳ１）。
続いて、二点間距離計算部１２ｂにより、記憶部１２ｅから読み出した距離データに基づいて距離データの隣り合う二点間の距離を算出する（ステップＳ２）。すなわち、角度分解能Δθのレーザレンジファインダ１１で取得した計測データのうち、それぞれ物体２を計測した隣り合う距離データｒi，ｒi+1に対し、二点間の距離ｌiを下式(3)により求める。
Next, the flow of local map creation by the local map creation unit 12 will be described with reference to FIG.
As shown in FIG. 3, in the local map creation unit 12, first, distance data acquired by the laser range finder 11 is input from the laser range finder 11 by the LRF data input unit 12a (step S1).
Subsequently, the distance between two adjacent points in the distance data is calculated by the distance calculation unit 12b between the two points based on the distance data read from the storage unit 12e (step S2). That is, among the measurement data acquired by the laser range finder 11 with the angular resolution Δθ, the distance l i between the two points is expressed by the following equation (3) with respect to the adjacent distance data r i and r i + 1 obtained by measuring the object 2 respectively. )
なお、角度分解能Δθが十分に小さい場合は、cosΔθ→１より、下式(4)により二点間の距離を求めることができる。 When the angular resolution Δθ is sufficiently small, the distance between the two points can be obtained from cos Δθ → 1 by the following equation (4).
ステップＳ２に続いては、ステップＳ２で求めた二点間の距離ｌiから二点間の「物体あり」の確率を算出する（ステップＳ３）。すなわち、上記ステップＳ２で求めた距離ｌiが短いほど「物体あり」（１．０）に近く、距離が長いほど「不明領域」の輝度（０．５）に近くなるように、以下の式(5)により二点間を接続する線の確率値ｐiを求める。 Following step S2, the probability of “object present” between the two points is calculated from the distance l i between the two points obtained in step S2 (step S3). That is, the following formula is set so that the shorter the distance l i obtained in step S2, the closer to “there is an object” (1.0), and the longer the distance l i , the closer to the luminance (0.5) of the “unknown area”. The probability value p i of the line connecting the two points is obtained by (5).
続いて、局所地図生成部１２ｄにより局所地図の生成を行う（ステップＳ４）。局所地図の生成は、図４に示すように局所地図全体を「不明領域Ａ」として輝度０．５で初期化した状態で、図５に示すように、「物体なし」領域描画部１２ｄａにより障害物がないところ、つまり隣り合う二つの計測点とレーザレンジファインダ１１の原点からなる三角形を「物体なし領域Ｂ」として輝度０．０で描画する（ステップＳ４ａ）。その後、図６に示すように、「物体あり」直線描画部１２ｄｂにより障害物があるところ、つまり隣り合う障害物計測点間を距離に基づいて算出した確率値ｐiに応じた部分を「物体あり領域Ｃ」として０．５より大きく１．０未満の輝度で直線状に描画する（ステップＳ４ｂ）。
以上により、局所地図の生成が終了する。
Subsequently, a local map is generated by the local map generator 12d (step S4). As shown in FIG. 4, the local map is generated by the “no object” area drawing unit 12da as shown in FIG. 5 in the state where the entire local map is initialized as “unknown area A” with a brightness of 0.5. Where there is no object, that is, a triangle composed of two measurement points adjacent to each other and the origin of the laser range finder 11 is drawn as “object-free region B” with a luminance of 0.0 (step S4a). After that, as shown in FIG. 6, where there is an obstacle by the “with object” straight line drawing unit 12db, that is, the part corresponding to the probability value p i calculated based on the distance between the adjacent obstacle measurement points is “object” As a “present area C”, a straight line is drawn with a luminance greater than 0.5 and less than 1.0 (step S4b).
This completes the generation of the local map.
ここで、図７は、分岐などで手前の物体と奥の物体との間で距離が大きく変化する場合の局所地図の例である。図７に破線で囲んで示すように、本実施例の局所地図作成装置を用いると、二点間の距離が大きく変化する部分は、ほぼ「不明領域Ａ」（輝度０．５）に近いグレーとなっていることが分かる。 Here, FIG. 7 is an example of a local map when the distance changes greatly between the front object and the back object due to branching or the like. As shown by a broken line in FIG. 7, when the local map creation device of the present embodiment is used, the portion where the distance between the two points greatly changes is a gray that is almost “unknown area A” (luminance 0.5). It turns out that it is.
上述した本実施例に係る局所地図作成装置および局所地図作成方法によれば、本来障害物がない部分を正確に「物体なし」と描画することができ、計測点間の距離が長い場合にはその長さに応じた輝度で「物体あり」を描画するため、上式(1)の間違いの割合をより正確に算出できることになる。
すなわち、レーザレンジファインダ１１のレーザー光１１ａの障害物２に対する照射角度Θが浅い場合であっても、「物体なし」の領域及び「物体あり」の領域を高精度に描画することができ、よって、大域地図を高精度に生成することが可能となる。
なお、上述した実施例では「不明領域Ａ」を輝度０．５で描画し、「物体なし領域Ｂ」を輝度０．０で描画し、「物体あり領域Ｃ」を０．５より大きく１．０未満の輝度で描画する例を示したが、例えば、「不明領域Ａ」及び「物体なし領域Ｂ」を予め設定された異なる色で描画し、「物体あり領域Ｃ」を二点間距離が小さいほど「物体あり領域Ｃ」に近く、二点間距離が大きいほど「不明領域Ａ」に近い色で描画するようにしてもよい。
According to the above-described local map creation device and local map creation method according to the present embodiment, a portion that does not originally have an obstacle can be accurately drawn as “no object”, and when the distance between measurement points is long Since “there is an object” is drawn with the luminance according to the length, the error rate of the above equation (1) can be calculated more accurately.
That is, even when the irradiation angle Θ of the laser beam 11a of the laser range finder 11 with respect to the obstacle 2 is shallow, the “no object” region and the “object present” region can be drawn with high accuracy. The global map can be generated with high accuracy.
In the above-described embodiment, the “unknown area A” is drawn with a luminance of 0.5, the “no object area B” is drawn with a luminance of 0.0, and the “object existence area C” is larger than 0.5. Although an example of drawing with a luminance of less than 0 has been shown, for example, “unknown area A” and “no object area B” are drawn in different preset colors, and “object with area C” has a distance between two points. The smaller the size, the closer to the “object presence region C”, and the larger the distance between the two points, the closer to the “unknown region A”.
本発明は、局所地図作成装置および局所地図作成方法に適用することができる。 The present invention can be applied to a local map creation device and a local map creation method.
１ ロボット
２ 物体
２ａ 障害物
２ｂ 壁
３ 局所地図
１１ レーザレンジファインダ（ＬＲＦ）
１１ａ レーザー光
１２ 局所地図作成部
１２ａ ＬＲＦデータ入力部
１２ｂ 二点間距離計算部
１２ｃ 二点間確率計算部
１２ｄ 局所地図生成部
１２ｄａ 「物体なし」領域描画部
１２ｄｂ 「物体あり」直線描画部
１２ｅ 記憶部
Ａ 不明領域
Ｂ 物体なし領域
Ｃ 物体あり領域
Ｄ 距離データ
Ｅ 扇形領域
Ｆ 未観測領域
Ｐ 障害物計測点
DESCRIPTION OF SYMBOLS 1 Robot 2 Object 2a Obstacle 2b Wall 3 Local map 11 Laser range finder (LRF)
11a Laser light 12 Local map creation unit 12a LRF data input unit 12b Two-point distance calculation unit 12c Two-point probability calculation unit 12d Local map generation unit 12da “No object” area drawing unit 12db “With object” straight line drawing unit 12e Storage Part A Unknown area B No object area C Object existing area D Distance data E Fan-shaped area F Unobserved area P Obstacle measurement point
Claims (4)
前記距離データに基づいて隣り合う二つの計測点間の距離を計算する二点間距離計算部と、
前記二つの計測点間の距離に基づいて隣り合う二つの計測点間に物体が存在する確率を計算する二点間確率計算部と、
前記距離データに基づいて物体の存在が不明な領域を予め設定した「不明領域」に対応する輝度で描画し、前記距離センサから前記計測点までの間を予め設定した「物体なし領域」に対応する輝度で描画する一方、隣り合う二つの計測点間を「物体あり領域」として前記確率に基づく値に応じた輝度で描画してグリッド状の局所地図を生成する局所地図生成部と
を備えることを特徴とする局所地図作成装置。 A distance data input unit for inputting distance data from a distance sensor that measures the distance radially at a constant angular interval;
A point-to-point distance calculation unit that calculates a distance between two adjacent measurement points based on the distance data;
A point-to-point probability calculation unit that calculates the probability that an object exists between two adjacent measurement points based on the distance between the two measurement points;
An area in which the presence of an object is unknown based on the distance data is drawn with a luminance corresponding to a preset “unknown area”, and a distance from the distance sensor to the measurement point is set in advance to correspond to a preset “no object area” A local map generation unit that generates a grid-like local map by drawing at a luminance according to a value based on the probability as a region between two adjacent measurement points as an “object-containing region” A local map creation device characterized by
ことを特徴とする請求項１記載の局所地図作成装置。 Based on the probability, the local map generation unit draws between two measurement points adjacent to each other with a luminance close to the “region with object” as the distance between the two measurement points adjacent to each other is shorter. 2. The local map creation device according to claim 1, wherein the distance between two measurement points is drawn with a brightness closer to the “unknown area” as the distance of is longer.
前記距離データに基づいて隣り合う二つの計測点間の距離を計算する第二の工程と、
前記二つの計測点間の距離に基づいて隣り合う二つの計測点間に物体が存在する確率を計算する第三の工程と、
前記距離データに基づいて物体の存在が不明な領域を予め設定した「不明領域」に対応する輝度で描画し、前記距離センサから前記計測点までの間を予め設定した「物体なし領域」に対応する輝度で描画する一方、隣り合う二つの計測点間を「物体あり領域」として前記確率に基づく値に応じた輝度で描画してグリッド状の局所地図を生成する第四の工程と
を備えることを特徴とする局所地図作成方法。 A first step of inputting distance data from a distance sensor that measures distances radially at constant angular intervals;
A second step of calculating a distance between two adjacent measurement points based on the distance data;
A third step of calculating a probability that an object exists between two adjacent measurement points based on a distance between the two measurement points;
An area in which the presence of an object is unknown based on the distance data is drawn with a luminance corresponding to a preset “unknown area”, and a distance from the distance sensor to the measurement point is set in advance to correspond to a preset “no object area” And a fourth step of generating a grid-like local map by drawing with a luminance according to the value based on the probability as a region between two adjacent measurement points as an “object-containing region”. A local map creation method characterized by
ことを特徴とする請求項３記載の局所地図作成方法。 In the fourth step, based on the probability, the shorter the distance between the two points is, the lower the distance between the two measurement points is drawn with the brightness close to the “object-containing region”. 4. The method for creating a local map according to claim 3, wherein the drawing is performed between two measurement points adjacent to each other with a brightness close to the "unknown area".
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011064821A1 (en) * | 2009-11-27 | 2011-06-03 | トヨタ自動車株式会社 | Autonomous moving object and control method |
| JP2015041203A (en) * | 2013-08-21 | 2015-03-02 | シャープ株式会社 | Autonomous moving body |
-
2015
- 2015-11-18 JP JP2015225492A patent/JP6601178B2/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011064821A1 (en) * | 2009-11-27 | 2011-06-03 | トヨタ自動車株式会社 | Autonomous moving object and control method |
| JP2015041203A (en) * | 2013-08-21 | 2015-03-02 | シャープ株式会社 | Autonomous moving body |
Non-Patent Citations (1)
| Title |
|---|
| 根岸 善朗: "全方位ステレオとレーザレンジファインダの統合による移動ロボットの地図生成", 日本ロボット学会誌, vol. 第２１巻 第６号, JPN6019034230, 15 September 2003 (2003-09-15), JP, pages 110 - 116, ISSN: 0004109477 * |
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|---|---|---|---|---|
| WO2019054209A1 (en) * | 2017-09-13 | 2019-03-21 | 日本電産シンポ株式会社 | Map creation system and map creation device |
| JPWO2019054209A1 (en) * | 2017-09-13 | 2020-10-29 | 日本電産シンポ株式会社 | Map making system and map making device |
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