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Dissertations / Theses on the topic 'Sampling-based motion planning'

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Published: 4 June 2021
Last updated: 14 March 2023

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1

Morales, Aguirre Marco Antonio. "Metrics for sampling-based motion planning." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2462.

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2

Bialkowski, Joshua John. "Optimizations for sampling-based motion planning algorithms." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87475.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 141-150).<br>Sampling-basedalgorithms solve the motion planning problem by successively solving several separate suproblems of reduced complexity. As a result, the efficiency of the sampling-based algorithm depends on the complexity of each of the algorithms used to solve the individual subproblems, namely the procedures GenerateSample, FindNearest, LocalPlan, CollisionFree, and AddToGraph. However, it is
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3

Jeon, Jeong hwan Ph D. Massachusetts Institute of Technology. "Sampling-based motion planning algorithms for dynamical systems." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/101443.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 133-143).<br>Dynamical systems bring further challenges to the problem of motion planning, by additionally complicating the computation of collision-free paths with collision-free dynamic motions. This dissertation proposes efficient approa
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4

Wedge, Nathan Alexander. "Sampling-based Motion Planning Algorithms: Analysis and Development." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1301502703.

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5

Evestedt, Niclas. "Sampling Based Motion Planning for Heavy Duty Autonomous Vehicles." Licentiate thesis, Linköpings universitet, Reglerteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-132769.

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The automotive industry is undergoing a revolution where the more traditional mechanical values are replaced by an ever increasing number of Advanced Driver Assistance Systems (ADAS) where advanced algorithms and software development are taking a bigger role. Increased safety, reduced emissions and the possibility of completely new business models are driving the development and most automotive companies have started projects that aim towards fully autonomous vehicles. For industrial applications that provide a closed environment, such as mining facilities, harbors, agriculture and airports, f
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6

Kunz, Tobias. "Time-optimal sampling-based motion planning for manipulators with acceleration limits." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53569.

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Robot actuators have physical limitations in how fast they can change their velocity. The more accurately planning algorithms consider these limitations, the better the robot is able to perform. Sampling-based algorithms have been successful in geometric domains, which ignore actuator limitations. They are simple, parameter-free, probabilistically complete and fast. Even though some algorithms like RRTs were specifically designed for kinodynamic problems, which take actuator limitations into account, they are less efficient in these domains or are, as we show, not probabilistically complete.
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7

Montana, Felipe. "Sampling-based algorithms for motion planning with temporal logic specifications." Thesis, University of Sheffield, 2019. http://etheses.whiterose.ac.uk/22637/.

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8

Rahman, S. M. Rayhan. "Performance of local planners with respect to sampling strategies in sampling-based motion planning." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=96891.

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Automatically planning the motion of rigid bodies moving in 3D by translation and rotation in the presence of obstacles has long been a research challenge for mathematicians, algorithm designers and roboticists. The field made dramatic progress with the introduction of the probabilistic and sampling-based "roadmap" approach. However, motion planning when narrow passages are present has remained a challenge. This thesis presents a framework for experimenting with combinations of sampling strategies and local planners, and for comparing their performance on user defined input problems. Our frame
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9

Luders, Brandon (Brandon Douglas). "Robust sampling-based motion planning for autonomous vehicles in uncertain environments." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90727.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2014.<br>CD-ROM has video of vehicle.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 223-237).<br>While navigating, autonomous vehicles often must overcome significant uncertainty in their understanding of the world around them. Real-world environments may be cluttered and highly dynamic, with uncertainty in both the current state and future evolution of environmental constraints. The vehicle may also face uncertainty in its own motion. To provide safe navi
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10

Pettersson, Per Olof. "Sampling-based Path Planning for an Autonomous Helicopter." Licentiate thesis, Linköping : Univ, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5270.

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11

Feng, Yu Yan, and Ziming Wang. "High-level Planning for Multi-agent System using a Sampling-based method." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-293839.

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One of the main focus of robotics is to integraterobotic tasks and motion planning, which has an increasedsignificance due to their growing number of application fieldsin transportation, navigation, warehouse management and muchmore. A crucial step towards this direction is to have robotsautomatically plan its trajectory to accomplish the given task.In this project a multi-layered approach was implemented toaccomplish it. Our framework consists of a discrete high-levelplanning layer that is designed for planning, and a continuouslow-level search layer that uses a sampling-based method for thet
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12

OSMAN, OSMAN ABDALLA SIDAHMED. "Autonomous Navigation for Unmanned Aerial Systems - Visual Perception and Motion Planning." Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2971114.

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13

Arslan, Oktay. "Machine learning and dynamic programming algorithms for motion planning and control." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54317.

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Robot motion planning is one of the central problems in robotics, and has received considerable amount of attention not only from roboticists but also from the control and artificial intelligence (AI) communities. Despite the different types of applications and physical properties of robotic systems, many high-level tasks of autonomous systems can be decomposed into subtasks which require point-to-point navigation while avoiding infeasible regions due to the obstacles in the workspace. This dissertation aims at developing a new class of sampling-based motion planning algorithms that are fast,
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14

Cowley, Edwe Gerrit. "Kinodynamic planning for a fixed-wing aircraft in dynamic, cluttered environments : a local planning method using implicitly-defined motion primitives." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/80077.

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Thesis (MScEng)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: In order to navigate dynamic, cluttered environments safely, fully autonomous Unmanned Aerial Vehicles (UAVs) are required to plan conflict-free trajectories between two states in position-time space efficiently and reliably. Kinodynamic planning for vehicles with non-holonomic dynamic constraints is an NP-hard problem which is usually addressed using sampling-based, probabilistically complete motion planning algorithms. These algorithms are often applied in conjunction with a finite set of simple geometric motion primi
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15

Fragkopoulos, Christos [Verfasser], Axel [Akademischer Betreuer] Gräser, and Kai [Akademischer Betreuer] Michels. "Automatic motion of manipulator using sampling based motion planning algorithms - application in service robotics / Christos Fragkopoulos. Gutachter: Axel Gräser ; Kai Michels. Betreuer: Axel Gräser." Bremen : Staats- und Universitätsbibliothek Bremen, 2014. http://d-nb.info/1072158019/34.

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16

Hwangbo, Myung. "Vision-Based Navigation for a Small Fixed-Wing Airplane in Urban Environment." Research Showcase @ CMU, 2012. http://repository.cmu.edu/dissertations/201.

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An urban operation of unmanned aerial vehicles (UAVs) demands a high level of autonomy for tasks presented in a cluttered environment. While fixed-wing UAVs are well suited for long-endurance missions at a high altitude, enabling them to navigate inside an urban area brings another level of challenges. Their inability to hover and low agility in motion cause more difficulties on finding a feasible path to move safely in a compact region, and the limited payload allows only low-grade sensors for state estimation and control. We address the problem of achieving vision-based autonomous navigation
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17

Němec, František. "Plánování pohybu objektu v 3D prostoru." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255428.

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This paper deals with the problem of object path planning in 3D space. The goal is to create program which allows users to create a scene used for path planning, perform the planning and finally visualize path in the scene. Work is focused on probabilistic algorithms that are described in the theoretical part. The practical part describes the design and implementation of application. Finally, several experiments are performed to compare the performance of different algorithms and demonstrate the functionality of the program.
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18

Johansson, Åke, and Joel Wikner. "Learning-Based Motion Planning and Control of a UGV With Unknown and Changing Dynamics." Thesis, Linköpings universitet, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176923.

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Research about unmanned ground vehicles (UGVs) has received an increased amount of attention in recent years, partly due to the many applications of UGVs in areas where it is inconvenient or impossible to have human operators, such as in mines or urban search and rescue. Two closely linked problems that arise when developing such vehicles are motion planning and control of the UGV. This thesis explores these subjects for a UGV with an unknown, and possibly time-variant, dynamical model. A framework is developed that includes three components: a machine learning algorithm to estimate the unknow
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19

Ahmad, Ahmad Ghandi. "Adaptive sampling-based motion planning with control barrier functions." Thesis, 2021. https://hdl.handle.net/2144/43120.

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In this thesis we modified a sampling-based motion planning algorithm to improve sampling efficiency. First, we modify the RRT* motion planning algorithm with a local motion planner that guarantees collision-free state trajectories without explicitly checking for collision with obstacles. The control trajectories are generated by solving a sequence of quadratic programs with Control Barrier Functions (CBF) constraints. If the control trajectories satisfy the CBF constraints, the state trajectories are guaranteed to stay in the free subset of the state space. Second, we use a stochastic optimiz
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20

Kumar, Sandip. "Generalized Sampling-Based Feedback Motion Planners." Thesis, 2011. http://hdl.handle.net/1969.1/ETD-TAMU-2011-12-10663.

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The motion planning problem can be formulated as a Markov decision process (MDP), if the uncertainties in the robot motion and environments can be modeled probabilistically. The complexity of solving these MDPs grow exponentially as the dimension of the problem increases and hence, it is nearly impossible to solve the problem even without constraints. Using hierarchical methods, these MDPs can be transformed into a semi-Markov decision process (SMDP) which only needs to be solved at certain landmark states. In the deterministic robotics motion planning community, sampling based algorithms like
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21

Burns, Brendan. "Exploiting structure: A guided approach to sampling-based robot motion planning." 2007. https://scholarworks.umass.edu/dissertations/AAI3275736.

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Robots already impact the way we understand our world and live our lives. However, their impact and use is limited by the skills they possess. Currently deployed autonomous robots lack the manipulation skills possessed by humans. To achieve general autonomy and applicability in the real world, robots must possess such skills. Autonomous manipulation requires algorithms that rapidly and reliably compute collision-free motion for robotic limbs with many degrees of freedom. Unfortunately, adequate algorithms for this task do not currently exist. Though there are many dimensions of the real-world
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22

Vasile, Cristian-Ioan. "Motion planning and control: a formal methods approach." Thesis, 2016. https://hdl.handle.net/2144/17081.

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Control of complex systems satisfying rich temporal specification has become an increasingly important research area in fields such as robotics, control, automotive, and manufacturing. Popular specification languages include temporal logics, such as Linear Temporal Logic (LTL) and Computational Tree Logic (CTL), which extend propositional logic to capture the temporal sequencing of system properties. The focus of this dissertation is on the control of high-dimensional systems and on timed specifications that impose explicit time bounds on the satisfaction of tasks. This work proposes and evalu
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23

Huang, Charly, and 黃昭霖. "Sampling-based Motion Planning with 3D Simultaneous Localization and Mapping for Social Aware Service Robotics Applications." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/41372898705061456057.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>104<br>In the present work, an socially aware autonomous navigation framework and motion planning algorithm for indoor service robot are proposed. The entirety of our work is based on Robot Operating System (ROS), which serves as the Linux-based middle-ware on which all robotics applications execute and communicate with each other based on an unified formats of messages, and allows sharing of information within a cluster of devices. Within ROS, our navigational framework consists of integrating layered planning scheme, layered costmap update (a ROS concept based on
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24

"Identifying Critical Regions for Robot Planning Using Convolutional Neural Networks." Master's thesis, 2019. http://hdl.handle.net/2286/R.I.53626.

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abstract: In this thesis, a new approach to learning-based planning is presented where critical regions of an environment with low probability measure are learned from a given set of motion plans. Critical regions are learned using convolutional neural networks (CNN) to improve sampling processes for motion planning (MP). In addition to an identification network, a new sampling-based motion planner, Learn and Link, is introduced. This planner leverages critical regions to overcome the limitations of uniform sampling while still maintaining guarantees of correctness inherent to sampling-based
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