Real-time path planning for navigation in unknown environment

Abstract

Real-time path planning is a challenging task that has many applications in the fields of AI, moving robots, virtual reality, agent behaviour simulation, and action games. The various approaches for path planning have different criteria that have to be met, resulting in a number of algorithms for solutions to specific problems. In this paper, we introduce our approach and recent development regarding path planning in game environments. We propose a novel real-time motionoptimisation algorithm called Adaptive Dynamic Points of Visibility (ADPV) for navigation of vehicles or moving agents in dynamical un-configured environments, which computes a collision-free, time-optimal motion track for the moving objects. Our approach is able to deal with the obstacle-space that is unknown or partially unknown to the moving agent. It therefore solves the drawbacks of traditional obstacle-space configuration methods.

Path Planning Based on Two-layer Adaptive Genetic Algorithm

“…The purpose of path planning for autonomous agent aims at generating a path with security, shorter, smooth and collision avoidance, and also provides agent the ability of sensing surrounding environment [1][2][3][4]. Genetic algorithm (GA) is a heuristic intelligent search algorithm that mimics the process of natural evolution.…”

“…represents the collision avoidance factor, as shown in Formula(1), where n denotes the number of path node, m denotes the number of obstacles within the sensing range of the agent, ikd denotes the distance between path node i p and the center point of the k-th obstacle, d s denotes the sum of the safety radius for the agent and obstacle. represents the evaluation of path length, as shown in obstacles, we introduced a penalty function i ω to punish the path length.…”

A Fuzzy Action Selection Method for Virtual Agent Navigation in Unknown Virtual Environments

“…The methods used are based on optimization and computational intelligence, for example, as in method [17]. On the other hand in an unknown environment in which the virtual agent does not have any knowledge about the environment, a method such as sensor based control in [18] uses Adaptive Dynamic Points of Visibility (ADPV) for moving agents in dynamical unconfigured environments. Other techniques used in solving the above problems are neural networks [19], learning [20] and evolutionary algorithms [21].…”

VLSI array architectures for navigation and human recognition in vision-guided embedded systems

“…However construction In [25], a sensor-based three-dimensional path planning algorithm was proposed to help underwater robotic vehicles perform real-time path planning in a static and unknown environment. An artificial immune network based path planning algorithm was proposed in [26] which is capable of achieving near-optimal collision free path in unknown environments that is presented by grids.…”