OBJECTIVE In this paper, we present an autonomous virtual mobile robot (AVMR) for three-dimensional (3D) exploration of unknown tubular-like structures in 3D images. METHODS AND MATERIALS The trajectory planning for 3D central navigation is achieved by combining two neuro-fuzzy controllers, and is based on 3D sensory information; a Hough transform is used to locally fit a cylinder during the ...

Path planning for an autonomous vehicle can occur at two different times. First, path planning might occur at mission specification time when the vehicle’s initial path is determined and used to specify other mission factors. This task makes use of some model of the environment in planning a path that will avoid obstacles and hazardous areas. A second type of path planning might occur while the...

We survey some of our recent work on real-time path planning and navigation of multiple autonomous agents in dynamic environments. The driving application of our work are real-time crowd simulation for computer games, virtual environments, and avatar-based online 3D social networks. We also present extensions to these methods for accelerating the overall simulation and for modeling more complex...

In this paper, we present SimHuman, a platform for the generation of real-time 3D environments with virtual agents. SimHuman is highly dynamic and configurable, as it is not based on fixed scenes and models, and has an embedded physically based modelling engine. Its agents can use features such as path finding, inverse kinematics and planning to achieve their goals. The paper explains in detail...

This paper describes an autonomous vehicle navigation system based on Velodyne LIDAR. The system mainly focusing on an autonomy at the car park, and it includes following functions, 1) odometory correction, 2) 3D map building, 3) localization, 4) detecting human trajectories as well as static obstacles, 5) path planning, and 6) vehicle control to a given trajectory. All those functions are deve...

The paper presents a framework for tracked vehicle 3D path planning in rough areas, with dynamic obstacles. The framework provides methods for real-time point cloud interpretation, segmentation and traversabilty analysis tacking also into account changes such as dynamic obstacles and provides a terrain structure interpretation. Moreover the paper presents R2A an extended version of randomized A...

This paper presents results from the 2006 and 2007 test campaigns of the Canadian Space Agency's autonomous rover navigation research. In particular, results are provided in the area of terrain modelling, path planning, and 3D odometry. Results are also provided for integrated system tests whereby the rover travelled autonomously and semi-autonomously beyond its sensing horizon. It provides a s...

This paper presents a traffic simulation system based on multi-agent animation method. The behaviour model of individual virtual agent defines the driving characteristics of the vehicle agent and cell-based configurations allow real-time dynamic path planning and efficient traffic flow simulations. By incorporating the advantages of discrete cellular automation algorithms and the continuous mod...

This paper presents a multilevel, posture-based motor control model intended to plan collision-free movements in a 3D environment while maintaining computationally efficiency and accurately imitating human and primate motor function. Our model is a comprehensive approach that addresses the storage and lookup of postures and movements, path planning and the generation of new movements, and learn...

In this paper, we show the results of applying stochastic sampling methods such as Cross Entropy method and Sampling Based Differential Dynamic Programming method to path planning of Unmanned Ground Vehicles (UGV) on unstructured 3D terrains. We show the superiority of sampling algorithms to local optimization methods such as Gauss Newton optimization method through simulations.A high fidelity ...