Abstract:
본발명의무인자율차량에는주행중인주변지형에대한환경정보를수집하는센서모듈(10)과, 주행중인현재위치를추정하는위치추정모듈(20)과, 수집한각종정보로부터현재속한주행로의환경인식에적합한알고리즘을선정하고주행정보를최신화하여유지하는주행정보모듈(30)과, 처리되어진환경인식결과를도출하는지형감지처리모듈(80)이포함되고, 위치정보(a)로부터환경인식결과에따른 QoSour(Quality of Service)의선정과지형감지정보(b)로부터알고리즘적합도결과에따른 QoSmax(Quality of Service)의선정이이루어지고, 이에Δ = QoSmax - QoSour 조건과Δ > a 조건을순차적으로적용해최적의주행알고리즘이선택됨으로써알고리즘은행(Bank)과서비스품질척도(Degree of Service Quality)로부터최적의알고리즘이선정되고, 특히이로부터환경인식성능척도갱신되는특징을갖는다.
Abstract:
An unmanned ground vehicle of the present invention includes a reference velocity generating block (30) for determining a slope, a first factor generating block (40) for determining a curvature, and a second factor block (50) for determining a stopping distance, and receives a final velocity (Vel), as a velocity command every moment, calculated by a fusion processing block (60) to which the results of processing of the other blocks, all the slope (sl), curvature (k), and stopping distance (sd), are inputted, thereby ensuring safety against risk factors during off-road driving.
Abstract:
Provided is an unmanned autonomous vehicle according to the present invention to which an autonomous running method in a dynamic environment is applied, wherein the autonomous running method comprises extracting a grid (Nbest) having the lowest assessment function value from an open list and surveying a probabilistic threat degree of the corresponding grid by a moving obstacle; recalculating the assessment function value of the Nbest if no threat degree has existed when the Nbest was inserted into the open list and the threat degree exists at this point in time due to the movement of the obstacle; recalculating the assessment function value for a grid having the thread degree among neighboring grids that have been previously detected or existed as candidates when performing an extension task of inserting the neighboring grids of the Nbest into the open list for route detection; recalculating the assessment function value for child grids of the neighboring grids using this, thereby, if a grid, where no threat degree of the obstacle has existed at the previous point in time, has a new threat degree by a movement of a moving obstacle at this point in time, performing a local route plan for the autonomous running of the unmanned vehicle by reflecting information like this.
Abstract:
PURPOSE: A driving information generating device of an unmanned vehicle, the unmanned vehicle comprising the same, and a controlling method thereof are provided to determine a driving path and a driving method by reflecting outer environmental information including map information. CONSTITUTION: A sensor(110) senses outer environment information. A driving information generating part(150) maps the outer environment information to stored map information to generate driving information. A driving information controlling part(170) use the position information of a main body and the driving information of the main body for determining at least one between a driving path and a driving method. [Reference numerals] (110) Sensor device; (120) Sensor information processing part; (130) Knowledge database part; (140) Location receiving part; (150) Driving information generating part; (160) Driving information database part; (170) Driving information controlling part; (180) Driving information providing part; (AA) Image navigation; (BB) Satellite navigation; (CC) Inertia navigation; (DD) Driving road DB; (EE) Intersection DB;
Abstract:
본발명의무인자율차량에는주행중인주변지형에대한환경정보를수집하는센서모듈(10)과, 주행중인현재위치를추정하는위치추정모듈(20)과, 수집한각종정보로부터현재속한주행로의환경인식에적합한알고리즘을선정하고주행정보를최신화하여유지하는주행정보모듈(30)과, 처리되어진환경인식결과를도출하는지형감지처리모듈(80)이포함되고, 위치정보(a)로부터환경인식결과에따른 QoSour(Quality of Service)의선정과지형감지정보(b)로부터알고리즘적합도결과에따른 QoSmax(Quality of Service)의선정이이루어지고, 이에Δ = QoSmax - QoSour 조건과Δ > a 조건을순차적으로적용해최적의주행알고리즘이선택됨으로써알고리즘은행(Bank)과서비스품질척도(Degree of Service Quality)로부터최적의알고리즘이선정되고, 특히이로부터환경인식성능척도갱신되는특징을갖는다.