Path planning is one of the most vital elements of mobile robotics, providing the agent with a collision-free route through the workspace. The global path plan can be calculated with a variety of informed search algorithms, most notably the A* search method, guaranteed to deliver a complete and optimal solution that minimizes the path cost. D* is widely used for its dynamic replanning capabilit...

SINCE typical mobile robotic vehicles have mobility sensors (such as LADAR or stereo) that can only acquire data up to a few tens of meters, a navigation system has no knowledge about the world beyond this sensing horizon. As a result, path planners that rely only on this knowledge to compute paths are unable to anticipate obstacles sufficiently early and has no choice than to plan inefficient ...

The probabilistic belief networks that result from standard feature-based simultaneous localization and map building (SLAM) approaches cannot be directly used to plan trajectories. The reason is that they produce a sparse graph of landmark estimates and their probabilistic relations, which is of little value to find collision free paths for navigation. In contrast, we argue in this paper that P...

347 Robust Path Planning in the Plane Fernando De la Rosa, Christian Laugier and Jos e N ajera Abstract|This work presents an approach to plan motion strategies for robotics tasks constrained by uncertainty in position, orientation and control. Our approach operates in a (x; y; ) con guration space and it combines two local functions: a contact-based attraction function and an exploration funct...

In this article, we present experiments studying path planning under spatial uncertainties. In the main experiment, the participants' task was to navigate the shortest possible path to find an object hidden in one of four places and to bring it to the final destination. The probability of finding the object (probability matrix) was different for each of the four places and varied between condit...

The University of Tulsa, among other research institutions, performs research exploring the possibility of using Genetic Algorithms (GA’s) to develop an algorithm for autonomous robot navigation. We have achieved significant success in this area. However, we encountered a problem. We realized there is no standard metric for comparing different algorithms developed by many researchers working in...

Animating goal-driven agents in an environment with obstacles is a time consuming process, particularly when the number of agents is large. In this paper, we introduce an efficient algorithm that creates path plans for objects that move between user defined goal points and avoids collisions. In addition, the system allows “culling” of some of the computation for invisible agents: agents are acc...

In this study, we first address the problem of visibility-based target tracking for a team of mobile observers trying to track a team of mobile targets. Initially, we introduce the notion of pursuit fields for a single observer to track a single target around a corner based on the previous work. Pursuit fields are used to generate navigation strategies for a single observer. In order to account...

Central problems in path planning are obstacle avoidance and path optimisation. The aim of our work was to investigate the efciency of an Evolution Strategy for optimising robot parameters in both respects. We chose a simple model in order to highlight the effect of evolution as an optimisation procedure. In our model the robot has to reach given goals from a given starting position. In our sim...

This paper introduces a simulation designed to test real-time path planning done by single and multiple agents. The components of the simulation include a road network, several Uninhabited Aerial Vehicles (UAVs) with electro-optic sensors, a target and an Uninhabited Ground Vehicle (UGV). The target and UGV are located on the road network. Random blockages are placed on the road network, possib...