In this work, a new algorithm for autonomous avatar motion is presented. The new algorithm is based in the Rapidly-exploring Random Tree (RRT) and an appropriate ontology. It uses a novel approach for calculating the motion sequence planning for the different avatar limbs: legs or arms. First, the algorithm uses the information stored in the ontology concerning the avatar structure and the Degr...

This work proposes to combine two main areas of the Artificial Intelligence which are: Computer vision and Motion Planning, to be incorporated in the area of aerial robotics through unmanned aerial robots. Our main objective is the tracking of people using the detection and tracking algorithms: HOG (Histogram of Oriented Gradients) and Particle Filter besides integrate it with motion planning f...

Rapidly-exploring random trees (RRTs) are data structures and search algorithms designed to be used in continuous path planning problems. They are one of the most successful state-of-the-art techniques in motion planning, as they offer a great degree of flexibility and reliability. However, their use in other fields in which search is a commonly used approach has not been thoroughly analyzed. I...

This survey studies asymptotics of random fringe trees and extended fringe trees in random trees that can be constructed as family trees of a Crump–Mode–Jagers branching process, stopped at a suitable time. This includes random recursive trees, preferential attachment trees, fragmentation trees, binary search trees and (more generally) m-ary search trees, as well as some other classes of random...

This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees v...

In this paper, we describe a planning and control approach in terms of sampling using Rapidly-exploring Random Trees (RRTs), which were introduced by LaValle. We review RRTs for motion planning and show how to use them to solve standard nonlinear control problems. We extend them to the case of hybrid systems and describe our modifications to LaValle’s Motion Strategy Library to allow for hybrid...

A randomized motion-planning approach to providing guidance for helicopters with under-slung loads is presented. Rapidly-exploring Random Trees are adapted to plan trajectories for simplified helicopter-load models. Four different planning models are tested against four different representative tasks. The poor performance of the baseline planner, and subsequent efforts to improve that performan...