Dynamic Path Planning of Mobile Robot Based on Improved Ant Colony Optimization Algorithm

Yang, Liang; Ma, Jianwei; Zang, Shaofei; Min, Yibo

doi:10.1145/3375998.3376018

Cited by 19 publications

(16 citation statements)

References 4 publications

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“…An application to mobile robotics can be seen in literature. 158 –161 Simulated annealing (SA) : The name and inspiration originated from annealing in metallurgy, a method that involves heating and controlled cooling of a material to boost the size of its crystals and reduce defects in it. The method of SA is based on a numerical technique that was proposed by Metropolis et al in 1953.…”

Section: Navigationmentioning

confidence: 99%

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A review of mobile robots: Concepts, methods, theoretical framework, and applications

Rubio

Chuliá

Llopis-Albert

2019

International Journal of Advanced Robotic Systems

454

178

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Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great examples of mobile robots. They can be distinguished from other robots by their ability to move autonomously, with enough intelligence to react and make decisions based on the perception they receive from the environment. Mobile robots must have some source of input data, some way of decoding that input, and a way of taking actions (including its own motion) to respond to a changing world. The need to sense and adapt to an unknown environment requires a powerful cognition system. Nowadays, there are mobile robots that can walk, run, jump, and so on like their biological counterparts. Several fields of robotics have arisen, such as wheeled mobile robots, legged robots, flying robots, robot vision, artificial intelligence, and so on, which involve different technological areas such as mechanics, electronics, and computer science. In this article, the world of mobile robots is explored including the new trends. These new trends are led by artificial intelligence, autonomous driving, network communication, cooperative work, nanorobotics, friendly human-robot interfaces, safe human-robot interaction, and emotion expression and perception. Furthermore, these news trends are applied to different fields such as medicine, health care, sports, ergonomics, industry, distribution of goods, and service robotics. These tendencies will keep going their evolution in the coming years.

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Section: Navigationmentioning

confidence: 99%

“…An application to mobile robotics can be seen in literature. 158 –161…”

Section: Navigationmentioning

confidence: 99%

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Rubio

Chuliá

Llopis-Albert

2019

International Journal of Advanced Robotic Systems

454

178

View full text Add to dashboard Cite

show abstract

“…Connell et al developed dynamic path planners [242] for mobile robots with replanning using RRT. Liu et al [243] developed a dynamic path planner using an improvized ant colony optimization algorithm. They simulate the algorithm on a grid map.…”

Section: Path Planningmentioning

confidence: 99%

Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

Kolar

Benavidez

Jamshidi

2020

Sensors

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This paper focuses on data fusion, which is fundamental to one of the most important modules in any autonomous system: perception. Over the past decade, there has been a surge in the usage of smart/autonomous mobility systems. Such systems can be used in various areas of life like safe mobility for the disabled, senior citizens, and so on and are dependent on accurate sensor information in order to function optimally. This information may be from a single sensor or a suite of sensors with the same or different modalities. We review various types of sensors, their data, and the need for fusion of the data with each other to output the best data for the task at hand, which in this case is autonomous navigation. In order to obtain such accurate data, we need to have optimal technology to read the sensor data, process the data, eliminate or at least reduce the noise and then use the data for the required tasks. We present a survey of the current data processing techniques that implement data fusion using different sensors like LiDAR that use light scan technology, stereo/depth cameras, Red Green Blue monocular (RGB) and Time-of-flight (TOF) cameras that use optical technology and review the efficiency of using fused data from multiple sensors rather than a single sensor in autonomous navigation tasks like mapping, obstacle detection, and avoidance or localization. This survey will provide sensor information to researchers who intend to accomplish the task of motion control of a robot and detail the use of LiDAR and cameras to accomplish robot navigation.

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“…Researchers have performed a large amount of research, using artificial neural networks [1],ant colony algorithm [2], and so on combined with fuzzy logic to achieve understanding and rapid classification of current environmental perceptions, the artificial potential field method [3], behavior dynamics [4], Firefly algorithm [5], full coverage path planning algorithm [6], lidar acquisition data and RBPF-SLAM [7] to construct maps, and other methods to solve the autonomous navigation problem in unknown environments for global planning of the robot path or for a combination of global and local planning [8][9][10]. Researchers combine behavior dynamics and rolling windows to perform path planning [11,12]; the local sub-objective is optimized by using a heuristic function according to the local information in the rolling window obtained by the robot; the behavior dynamics model is used to perform autonomous path planning [13] in the rolling windows; and the planning trajectory of a series of windows is connected end to end to realize the global path planning. Behavior dynamics uses point attractor and point repulsor to build robot behavior, and the robot's heading angle and motion speed are used as behavior variables to describe robots moving in a plane [14], but in the application, the line speed is limited by the heading angular velocity control and causes a deadlock; in addition, because of the non additivity of the virtual forces, there are also pseudo attractor problems.…”

Section: Introductionmentioning

confidence: 99%

Indoor robot path planning assisted by wireless network

Wang

Nie

Zhu

2019

J Wireless Com Network

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Indoor robot global path planning needs to complete the motion between the starting point and the target point according to robot position command transmitted by the wireless network. Behavior dynamics and rolling windows in global path planning methods have limitations in their applications because the path may not be optimal, there could be a pseudo attractor or blind search in an environment with a large state space, there could be an environment where offline learning is not applicable to real-time changes, or there could be a need to set the probability of selecting the robot action. To solve these problems, we propose a behavior dynamics and rolling windows approach to a path planning which is based on online reinforcement learning. It applies Q learning to optimize the behavior dynamics model parameters to improve the performance, behavior dynamics guides the learning process of Q learning and improves learning efficiency, and each round of intensive learning action selection knowledge is gradually corrected as the Q table is updated. The learning process is optimized. The simulation results show that this method has achieved remarkable improvement in path planning. And, in the actual experiment, the robot obtains the target location information by wireless network, and plans an optimized and smooth global path online.

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Dynamic Path Planning of Mobile Robot Based on Improved Ant Colony Optimization Algorithm

Cited by 19 publications

References 4 publications

A review of mobile robots: Concepts, methods, theoretical framework, and applications

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Survey of Datafusion Techniques for Laser and Vision Based Sensor Integration for Autonomous Navigation

Indoor robot path planning assisted by wireless network

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