Trajectory planning and tracking for autonomous vehicles

Download

index.pdf

Date

2022-12-27

Author

Çiçek, Haluk Levent

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

322
views

239
downloads

Finding appropriate paths is an essential issue for the development of autonomous vehicles and robots. Hereby, it has to be considered that autonomous vehicles cannot follow sharp corners, as they cannot turn on a single point. Therefore, it is important to compute smooth paths that have additional desirable properties such as minimum length and sufficient distance from obstacles. Furthermore, practical applications require the computation of such paths in real time. This thesis develops a general method for path planning and tracking of autonomous vehicles. In line with the stated requirements, the proposed algorithm ensures smooth curves and avoids sharp corners on the planned path. The proposed algorithm is based on different existing path planning algorithm which named as the Voronoi Boundary Visibilty and Steiner Points Repeatedly (VV-ST-R) that result in straight-line paths with corners. The undesired sharp corners resulting from these algorithm are replaced by smooth curves using Bezier curves. In this way, the traceability of the road is increased. As performance criteria, the path's calculation time, the shortest path distance to the obstacle, and the total length of the path are determined. In various computational experiments, the proposed algorithm and the previous algorithm are compared. In addition, proposed method for choosing Bezier curve control points are evaluated. It is found that the proposed algorithm results in short smooth paths with a sufficient obstacle distance and a small computation time. Finally, the traceability of the proposed paths is confirmed by driving simulations with car-like robots using the Pure Pursuit algorithm for path tracking. It is further expected that the proposed method can be used for both road vehicles and mobile robots.

Subject Keywords

Path planning, Tracking, Autonomous vehicles, Mobile robots, Bezier Curves

URI

https://hdl.handle.net/11511/101914

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

LOCALIZATION PERFORMANCE ESTIMATION WITH MULTI SENSOR FUSION Bingöl, Ulaş Süreyya; Ankaralı, Mustafa Mert; Hacınecipoğlu, Akif; Department of Electrical and Electronics Engineering (2022-5-12) Autonomous navigation gained significant attention as it is necessary for an over- growing use and integration of autonomous systems to numerous fields such as self- driving cars, logistics, and agricultural robots. These applications require robots to navigate from one location to another, which requires them to estimate their position accurately. Localization loss scenarios are instances when localization accuracy dete- riorates to a level that endangers the task. Reaching the false end goals, being stuck...
Human aware navigation of a mobile robot in crowded dynamic environments Hacınecipoğlu, Akif; Konukseven, Erhan İlhan; Department of Mechanical Engineering (2019) As mobile robots start operating in dynamic environments crowded with humans, human-aware and human-like navigation is required to make these robots navigate safely, efficiently and in socially compliant manner. People can navigate in an interactive and cooperative fashion so that, they are able to find their path to a destination even if there is no clear path leading to it. This is clearly a dexterity of humans. But the mobile robots which have to navigate in such environments lack this feature. Even perf...
Sensor based planning: A control law for generating the generalized Voronoi graph Choset, H; Konukseven, Erhan İlhan; Rizzi, A (1997-01-01) We introduce a new control law for robots that explore unknown environments and configuration spaces. Unlike numerical continuation methods, which produce a jagged path because of the predictor-corrector approach, the control law, introduced in this paper, performs sensor based planning by directing the head of a robot to follow continuously a roadmap. Recall that a roadmap is a one-dimensional representation of a robot's environment. Once the robot exhaustively traces out the roadmap using this control law...
The learning and use of traversability affordance using range images on a mobile robot Ugur, Emre; Dogar, Mehmet R.; Cakmak, Maya; Şahin, Erol (2007-04-14) We are interested in how the concept of affordances can affect our view to autonomous robot control, and how the results obtained from autonomous robotics can be reflected back upon the discussion and studies on the concept of affordances. In this paper, we studied how a mobile robot, equipped with a 3D laser scanner, can learn to perceive the traversability affordance and use it to wander in a room filled with spheres, cylinders and boxes. The results showed that after learning, the robot can wander around...
Feedback Motion Planning For a Dynamic Car Model via Random Sequential Composition Özcan, Melih; Ankaralı, Mustafa Mert (2019-01-01) Autonomous cars and car-like robots have gained huge popularity recently due to the recent advancements in technology and AI industry. Motion and path planning is one of the most fundamental problems for such systems. In the literature, kinematic models are widely adopted for planning and control for these type of robots due to their simplicity (control and analysis) and fewer computational requirements. Though, applicability of kinematic models are limited to very low speeds or some specific cases, which c...

Citation Formats

H. L. Çiçek, “Trajectory planning and tracking for autonomous vehicles,” M.S. - Master of Science, Middle East Technical University, 2022.