Rapidly exploring random trees (RRT) and probabilistic roadmaps (PRM) are sampling-based techniques being extensively used for robot path planning. In this paper, the tree structure of the RRT is generalized to a graph structure which enables a greater exploration. Exploration takes place ...
Instead of applying time-complex force-directed edge bundling, we adopt the concept of Rapidly-Exploring Random Trees (RRTs). We use RRTs for fast computation of a hierarchical space organization that is independent of the spatial structure of the graph layout. Due to this independency, edge ...
wherezis a known parameter (see “Methods” to learn what values ofzcan be used). A contiguous region is defined as any connected subgraph of the defined nearest neighbor graph, i.e., between each two nodes in the contiguous region, there is at least one connecting path. (vii) For simpl...
In future research, we are setting our sights on exploring and developing more sophisticated network architectures with the intent to significantly boost the efficiency and generalization capabilities of our model. We are particularly interested in graph neural networks, as they offer a unique approach ...
Animal genomes contain thousands of long noncoding RNA (lncRNA) genes, a growing subset of which are thought to be functionally important. This functionality is often mediated by short sequence elements scattered throughout the RNA sequence that correspo
FAIGL J.On Self-Organizing Map and Rapidly-Exploring Random Graph in Multi-Goal Planning[M].New York:Springer International Publishing,2016.J. Faigl, "On self-organizing map and rapidly-exploring random graph in multi-goal planning," in Advances in Self-Organizing Maps and Learning Vector ...
resolution-complete rapidly-exploring random treestrajectory designhigh-dimensional systemsnonconvex constraintsresolution completeness analysisLipschitz conditionaccessibility graphTrajectory design for high-dimensional systems with nonconvex constraints has considerable success recently; however, the resolution ...
In this work, we present Dynamic Region-biased RRT, a novel samplingbased planner that guides the exploration of a Rapidly-exploring Random Tree (RRT) by moving sampling regions along an embedded graph that captures the workspace topology. These sampling regions are dynamically created, manipulated,...
The traditional rapidly exploring random tree (RRT) algorithm [21] constructs a search random tree based on the initial pose and target pose obtained from the scene map. A schematic diagram of the RRT algorithm is shown in Figure 2. The starting point serves as the root node of the random...
Therefore, this work aims to advance a methodology for online adaptive path planning based on the fusion of rapidly exploring random trees (RRT) and deep reinforcement learning (DRL) applied to unmanned aerial vehicles. This research considers an olive-growing environment to assess the proposed metho...