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 19 of 19 for “"Rapidly exploring random trees"”.
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Information-rich path planning under general constraints using Rapidly-exploring Random Trees
This thesis introduces the Information-rich Rapidly-exploring Random Tree (IRRT), an extension of the RRT algorithm that embeds information collection as predicted using Fisher information matrices. The primary contribution of this trajectory generation algorithm is target-based information …
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Decentralized path planning for multiple agents in complex environments using rapidly-exploring random trees
… developed, the Decentralized Multi-Agent Rapidly-exploring Random Tree (DMARRT) algorithm, is an extension of the CL-RRT algorithm to the multi-agent case, retaining its ability to plan quickly even with complex constraints. Moreover, a merit-based token passing coordination strategy is …
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Path planning for autonomous parafoils using particle chance constrained rapidly-exploring random trees in a computationally constrained environment
Particle chance constrained rapidly-exploring random trees (PCC-RRT) is a sampling-based path-planning algorithm which uses particles to approximate an uncertainty distribution. In this thesis, we study the use of PCC-RRT on an autonomous parafoil. Specifically, we explore the behavior of PCC-RRT …
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Efficient nearest-neighbor search algorithms for sub-Riemannian geometries
… such as Probabilistic Road Maps (PRMs), Rapidly-exploring Random Trees (RRTs) and a large number of variants thereof. In this thesis, we focus on a crucial building block shared by these algorithms: nearest-neighbor search. While nearest-neighbor search is known as the asymptotically …
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A perception-guided approach to motion and manipulation planning
Rapidly-Exploring Random Trees (RRT) have been successfully applied to many different robotics systems for motion and manipulation planning under non-holonomic constraints. However, the conventional RRT algorithm may perform poorly in the presence of noise and uncertainty. This thesis proposes a …
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Obstacle Detection and Avoidance System for Unmanned Aerial Vehicles Based on Monocular Camera
… around large, static objects like buildings or trees. However, detecting small objects and handling dynamic aerial environments remain challenging. To address this, we introduce an innovative system for small object detection and real-time path planning using a monocular camera. Our dual-stage …
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Obstacle Avoidance for Small Unmanned Air Vehicles
… to avoid obstacles. This research compares rapidly-exploring random trees to genetic algorithms for UAV pre-mission path planning. It also presents two methods for using image feature movement and UAV telemetry to calculate depth and detect obstacles. The first method uses pixel ray …
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Sampling-based path planner for guided airdrop in urban environments
… parafoil terminal guidance. The algorithm uses Rapidly-Exploring Random Trees (RRT) to efficiently search for feasible paths through complex environments. Most importantly, Rewire-RRT provides a mechanism to build and rewire the tree to explicitly minimize the risk of collision with obstacles …
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Modeling and control of a robot manipulator
… used as a test platform. Three versions of the Rapidly-exploring Random Trees planning algorithm namely, basic RRT, RRT Ball and RRT_ are compared. Results obtained show that RRT_ is more suitable than RRT and RRT Ball in terms of the length and the consistency of the trajectories produced. A …
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Surveying Underwater Shipwrecks with Probabilistic Roadmaps
… by a probabilistic roadmap algorithm that uses a rapidly-exploring random tree to quickly cover the volume of exploration space and generate small maps with good coverage. The roadmap is constructed out of nodes, each having its own weight. The weight of a given node is calculated using an …
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Multi-Robot Path Planning Using Sampling-Based Algorithms and Reinforcement Learning
… puts sampling-based algorithms such as RRT (Rapidly-exploring Random Trees), RRT*, and M* to the test to determine which has the best performance in terms of time spent developing and executing the path plan, overall path plan route length, completion success rate, and scalability to more …
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Nonlinear trajectory optimization with path constraints applied to spacecraft reconfiguration maneuvers
… differential constraints and solved using Rapidly-exploring Random Trees (RRT's). The improvement step is posed as a feasible nonlinear optimization problem and solved by an iterative optimization similar to a sequential linear programming method. The primary contribution of the thesis is …
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Motion Planning For Autonomous Vehicles In Non-Signalized Intersections
… flow, which raises the risk of accidents. Rapidly Exploring Random Trees (RRT) is a widely adopted algorithm in robotics for motion planning due to its simplicity and probabilistic completeness. Over the years, researchers have made modifications to the basic RRT algorithm to improve its …
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Learning Probabilistic Generative Models For Fast Sampling-Based Planning
… based on Gaussian Mixture Models (GMMs) for Rapidly-exploring Random Trees (RRT). In addition, we introduce a new probabilistically safe local steering primitive based on the probabilistic model. Our local steering procedure is based on a new notion of a convex probabilistically safety …
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Robust sampling-based motion planning for autonomous vehicles in uncertain environments
… 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 motion planning framework capable of generating feasible paths for autonomous vehicles in complex …
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Analytic chance constraints for the robust guidance of autonomous parafoils
… builds upon the framework of chance-constrained rapidly-exploring random trees (CC-RRT). This planner enables fast incremental trajectory construction in cluttered, non-convex environments, while using chance constraints to ensure probabilistic feasibility. The designed cost-to-go function …
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Threat assessment for safe navigation in environments with uncertainty in predictability
… The proposed approach, RR-GP, combines the Rapidly-exploring Random Trees (RRT) based algorithm, RRT-Reach, with mixtures of Gaussian Processes (GP) to compute dynamically feasible paths, in real-time, while embedding the flexibility of GP's nonparametric Bayesian model. RR-GP efficiently …
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Feynman-Kac Numerical Techniques for Stochastic Optimal Control
Three significant advancements are proposed for improving numerical methods in the solution of forward-backward stochastic differential equations (FBSDEs) appearing in the Feynman-Kac representation of the value function in stochastic optimal control (SOC) problems. First, we propose a novel …
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On-Board Artificial Intelligence for Failure Detection and Safe Trajectory Generation
… in combination with the multi-goal Rapidly-Exploring Random Tree (RRT*) path planning algorithm to generate safe trajectories based on a reduced flight envelope. A high-fidelity model of a fixed-wing unmanned aerial vehicle is used to demonstrate the capabilities of the approach by …