Istraživanje i modeliranje nepoznatog poligonalnog prostora zasnovano na nesigurnim podacima udaljenosti

We consider problem of exploration and mapping of unknown indoor environments using laser range finder. We assume a setup with a resolved localization problem and known uncertainty sensor models. Most exploration algorithms are based on detection of a boundary between explored and unexplored regions. They are, however, not efficient in practice due to uncertainties in measurement, localization and map building. The exploration and mapping algorithm is proposed that extends Ekman’s exploration algorithm by removing rigid constraints on the range sensor and robot localization. The proposed algorithm includes line extraction algorithm developed by Pfister, which incorporates noise models of the range sensor and robot’s pose uncertainty. A line representation of the range data is used for creating polygon that represents explored region from each measurement pose. The polygon edges that do not correspond to real environmental features are candidates for a new measurement pose. A general polygon clipping algorithm is used to obtain the total explored region as the union of polygons from different measurement poses. The proposed algorithm is tested and compared to the Ekman’s algorithm by simulations and experimentally on a Pioneer 3DX mobile robot equipped with SICK LMS-200 laser range finder.Razmatramo problem istraživanja i izgradnje karte nepoznatog unutarnjeg prostora koristeći laserski sensor udaljenosti. Pretpostavljamo riješenu lokalizaciju robota i poznati model nesigurnosti senzora. Većna se algoritama istraživanja zasniva na otkrivanju granica istraženog i neistraženog područja. Međutim, u praksi nisu učinkoviti zbog nesigurnosti mjerenja, lokalizacije i izgradnje karte. Razvijen je algoritam istraživanja i izgradnje karte koji proširuje Ekmanov algoritam uklanjanjem strogih ograničenja na senzor udaljenosti i lokalizaciju robota. Razvijeni algoritam uključuje algoritam izdvajanja linijskih segmenata prema Pfisteru, koji uzima u obzir utjecaje zašumljenosti senzora i nesigurnosti položaja mobilnog robota. Linijska reprezentacija podataka udaljenosti koristi se za stvaranje poligona koji predstavlja istraženo područje iz svakog mjernog položaja. Bridovi poligona koji se ne podudaraju sa stvarnim značajkama prostora su kandidati za novi mjerni položaj. Algoritam općenitog isijecanja poligona korišten je za dobivanje ukupnog istraženog područja kao unija poligona iz različitih mjernih položaja. Razvijeni algoritam testiran je i uspoređen s izvornim Ekmanovim algoritmom simulacijski i eksperimentalno na mobilnom robotu Pioneer 3DX opremljenim laserskim senzorom udaljenosti SICK LMS-200

Motion planning of autonomous mobile robots in dynamic and unknown indoor environments

U ovom je radu istražen problem planiranja gibanja autonomnih mobilnih robota u dinamičkim i nepoznatim unutarnjim prostorima s posebnim naglaskom na algoritme prikladne za rad u stvarnom vremenu koji osiguravaju učinkovito gibanje robota uz zajamčeno izbjegavanje gibajućih prepreka u prostoru. Razvijen je algoritam planiranja geometrijske putanje zasnovan na mrežastoj karti zauzeća koji izračunava najkraću putanju u geometrijskom prostoru. Razvijen je algoritam izgradnje hijerarhijske karte prostora te algoritam hijerarhijskog planiranja putanje čime je osigurano planiranje gibanja mobilnog robota u stvarnom vremenu u velikim unutarnjim prostorima. Problem planiranja gibanja mobilnog robota u nepoznatim prostorima riješen je razvijenim algoritmom istraživanja prostora kojime je postignuta konvergencija algoritma istraživanja u realnim uvjetima. Opisane su metode slijeđenja isplanirane putanje, zasnovane na algoritmu dinamičkog prozora, koje proračunavaju moguće trajektorije s obzirom na kinematička i dinamička ograničenja robota. Uveden je kriterij objedinjavanja algoritma planiranja putanje i algoritma dinamičkog prozora. Razvijenim objedinjenim algoritmom planiranja gibanja osigurano je sigurno i glatko gibanje bez zastoja među statičkim i gibajućim preprekama. Naposlijetku, razvijen je algoritam planiranja gibanja zasnovan na konceptu pomičnog horizonta, za koji je dokazana asimptotska stabilnost ciljne točke korištenjem Ljapunovljeve analize stabilnosti. Svi su predloženi algoritmi testirani simulacijski i eksperimentalno na stvarnom robotu.This thesis focuses on the problem of path planning for autonomous mobile robots in dynamic and unknown indoor environment. Special emphasis is set on algorithms suitable for real-time applications which should ensure the efficient movement of a robot with guaranteed moving obstacles avoidance in the environment. A path planning algorithm based on the grid map that calculates the shortest path in the geometric space is proposed. An algorithm of automatic creation of the hierarchical graph is proposed together with the hierarchical path planning algorithm suitable for mobile robot's motion in real-time in a complex indoor environment. The problem of motion planning of mobile robot in unknown environment is solved by the proposed exploration algorithm, by which convergence of the exploration task in real terms is achieved. The path following methods based on dynamic window approach are considered, which take into account kinematic and dynamic constraints of the robot. The criterion for integration of the path planning algorithm and the dynamic window algorithm is introduced. The integrated motion planning algorithm is proposed which ensures a safe and smooth motion among moving obstacles. Finally, the motion planning algorithm based on the concept of receding horizon control is proposed, for which asymptotic stability of the goal point is proven via Lyapunov stability analysis. All proposed algorithms are tested by simulation and experimentally on a real robot in laboratory environments