O3: An optimal and opportunistic path planner (with obstacle avoidance) using voronoi polygons

Abstract

Abstract-Traditional mobile robot research focuses on a robot navigating its environment to reach a single goal while avoiding obstacles. This paper proposes a new method called O 3 to solve the challenges presented at the Intelligent Ground Vehicle Competition (IGVC) where a navigation course includes multiple goals to be found in an optimal order. The O 3 technique includes improvements on traditional path planning and obstacle avoidance techniques while providing an explicit ability to change course as obstacles are discovered. This method uses modern trajectories such as minimum-weighted Hamiltonian circuits, A* algorithm for obstacle avoidance, and local points of opportunity to update the globally optimal path using Voronoi polygons. Environmental mapping is also used to speed up the search algorithms in static environments. Overall, the O 3 technique exploits local points of opportunity while avoiding obstacles and ultimately finding a globally optimal path through an unknown environment.This methodology will be implemented on an autonomous web-based tour guide robot to serve the Internet community reviewing Elizabethtown College. This methodology can be extended to other research areas where multiple locations need to be traversed independent of their order such as city map, trip planners, and distribution networks (power, internet, etc) due to its balance between weighted graphs and obstacle avoidance (objects, traffic, construction, etc).

Innovative Piloting Technique for a Semi-Autonomous UAV Lighter-Than-Air Platform Simulator

“…Mathematically speaking, the majority of the trajectory generation methods consist of different ways of connecting together pre-determined potential flight segments into an optimal or near-optimal path. These include using a Hybrid A* algorithm 17 , Voroni polygons 18 , probabilistic maps 19 and other graphical methods 20 . Some researchers are also experimenting with various analytical techniques to solve these path-planning problems, including singular perturbation 21 , genetic algorithms 22 and neighbouring optimal control 23 as well as other optimization techniques, such as the Sequential Quadratic Programming 24 method.…”

Obstacle Avoidance System for Autonomous Vehicles

“…Multiple classical control approaches have been presented in literature for obstacle avoidance of Autonomous Vehicles e.g. Optimal Control [2] [3] [4], Model Predictive Control [5] [6] [7], Fuzzy Logic Systems [8] [9] etc. Moreover, Reinforcement Learning based obstacle avoidance has also been explored by various researchers.…”

3d Path Planning for Unmanned Aerial Vehicles Using Visibility Line Based Method

“…They have produced many methods and algorithms under several categories. Among them are geometric-based (Omar and Gu, 2009;Coleman and Wunderlich, 2008;Tian et al, 2007;Bortoff, 2000;Nilsson, 1984), grid-based (Chen et al, 1995;LingelBach, 2004) and potential field (Garibotto and Masciangelo, 1991;Barraquand et al, 1992), to name but three. One of the popular methods is geometricbased category under which there is an approach called visibility lines (VL).…”