Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 14 of 14 for “"Sampling Based Motion Planning"”.
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Sampling-Based Motion Planning With Differential Constraints
… of robotic systems are ignored in path planning, solutions for kinodynamic and non-holonomic planning problems from classical methods could be either inexecutable or inefficient. Motion planning with differential constraints (MPD), which directly considers differential constraints, …
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Optimizations for sampling-based motion planning algorithms
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 …
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Sampling-based motion planning algorithms for 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 approaches for the optimal sampling-based motion planning algorithms, with a strong …
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Robust sampling-based motion planning for autonomous vehicles in uncertain environments
… The vehicle may also face uncertainty in its own motion. To provide safe navigation under such conditions, motion planning algorithms must be able to rapidly generate smooth, certifiably robust trajectories in real-time. The primary contribution of this thesis is the development of a real-time …
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Improving Protein Conformational Sampling by Using Guiding Projections
… we study the conformational space of proteins. Sampling-based motion planning algorithms from the eld of robotics have been very successful at this task. However, studying the conformational space of large proteins with hundreds or thousands of Degrees of Freedom remains a big challenge. In this …
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Sampling and Searching Methods for Practical Motion Planning Algorithms
In its original conception, the motion planning problem considered the search of a robot path from an initial to a goal configuration. The study of motion planning has advanced significantly in recent years, in large part due to the development of highly successful sampling and searching …
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A robust motion planning approach for autonomous driving in urban areas
This thesis presents an improved sampling-based motion planning algorithm, Robust RRT, that is designed specifically for large robotic vehicles and uncertain, dynamic environments. Five main extensions have been made to the original RRT algorithm to improve performance in this type of applications. …
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Algorithms for autonomous urban navigation with formal specifications
This thesis addresses problems in planning and control of autonomous agents. The central theme of this work is that integration of "low-level control synthesis" and "high-level decision making" is essential to devise robust algorithms with provable guarantees on performance. We pursue two main …
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Learning Probabilistic Generative Models For Fast Sampling-Based Planning
… and efficiency in high dimensional space, sampling-based motion planners have been gaining interest for robotic manipulation in recent years. We present several new learning approaches using probabilistic generative models for fast sampling-based planning. First, we propose fast collision …
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Leveraging Structure for Efficient and Dexterous Contact-Rich Manipulation
… exhaustively, or compute-heavy and inefficient sampling methods that utilize blackbox optimization such as Reinforcement Learning (RL). In this thesis, I aim to show that by combining structured contact smoothing in conjunction with local gradient-based control and sampling-based motion …
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Robust motion planning for autonomous tracked vehicles in deformable terrain
… vehicle system significantly. In such cases, the motion planning of the autonomous vehicle must be performed robustly, considering the uncertain factors in advance of the real-time navigation. The primary contribution of this thesis is to present a robust optimal global planner for autonomous …
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Sampling-based algorithms for optimal path planning problems
Sampling-based motion planning received increasing attention during the last decade. In particular, some of the leading paradigms, such the Probabilistic RoadMap (PRM) and the Rapidly-exploring Random Tree (RRT) algorithms, have been demonstrated on several robotic platforms, and found applications …
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A framework for guided motion planning
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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Autonomous Navigation for Unmanned Aerial Systems - Visual Perception and Motion Planning
L'abstract è presente nell'allegato / the abstract is in the attachment