Simple Global Path Planning Algorithm Using a Ray-Casting and Tracking Method

Kim, In-Seok; Lee, Woong-Ki; Hong, Young-Dae

doi:10.1007/s10846-017-0642-2

Cited by 7 publications

(2 citation statements)

References 15 publications

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“…Robot navigation, a current trending topic to work on, is used in variety of operations to enhance efficiency in challenging circumstances. Various algorithms have been proposed in mobile robot path navigation and path planning (Kong et al, 2013;Pang et al, 2016;Liu et al, 2017;Panda et al, 2017;Geng et al, 2014;Seegmiller and Kelly, 2016;Kim et al, 2018;Wu and Karkoub, 2019;Clemente et al, 2017;Quillen and Subbara, 2018).These algorithms are functional with essential sensor information. In different situations, sensors gather the necessary information for the system including its location and direction information to estimate updated position.…”

Section: Introductionmentioning

confidence: 99%

Obstacle-avoiding intelligent algorithm for quad wheel robot path navigation

Mukherjee

Kumar

Borah

2020

IJIUS

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PurposeThe purpose of this work is to propose quad wheel robot with path navigation using an intelligent novel algorithm named as obstacle-avoiding intelligent algorithm (OAIA).Design/methodology/approachThe paper proposes OAIA algorithm, which is used to minimize the path distance and elapsed time between source and goal.FindingsThe hardware implementation of the Quad Wheel Robot design includes a global positioning system (GPS) module for path navigation. An ultrasonic module (HC SR04) is mainly used as the sensing unit for the system. In the proposed scheme, the GPS locator (L80) is used to obtain the current location of the robot, and the ultrasonic sensor is utilized to avoid the obstacles. An ARM processor serves as the heart of the Quad Wheel Robot.Practical implicationsThis paper includes real-time implementation of quad wheel robot for various coordinate values, and the movement of the robot is captured and analysed.Originality/valueThe proposed OAIA is capable of estimating the mobile robot position exactly under ideal circumstances. Simulation and hardware implementation are carried out to evaluate the performance of the proposed system.

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Section: Introductionmentioning

confidence: 99%

Obstacle-avoiding intelligent algorithm for quad wheel robot path navigation

Mukherjee

Kumar

Borah

2020

IJIUS

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“…Zhu et al (2017) establish an optimal path using A* algorithm in a grid arena by designing visual graphs in a global environment. Kim et al propose a simple global path planning algorithm based on ray casting and tracking method (Kim et al (2018) for tracing a competent path. Singh et al developed a fuzzy inference system for mobile robot navigation in a static environment (Singh and Thongam, 2018).…”

Section: Introductionmentioning

confidence: 99%

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

Parhi

Chhotray

2018

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Purpose This paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR). Design/methodology/approach This TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters. Findings Authenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%. Practical implications This robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform. Originality/value A new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

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Path planning of mobile robot in dynamic environment: fuzzy artificial potential field and extensible neural network

Wang

Chen

Zhang

et al. 2020

Artif Life Robotics

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Path planning in dynamic environment is a great challenge for mobile robot. A large number of approaches have been used to deal with it. Since the neural network algorithm has the ability to find the optimal solution at high speed and self-learning function, it has achieved extensive applications in the path planning tasks. Considering that the optimization performance of the neural network heavily depends on the quality of the training sample, this paper proposes a novel way to provide the training samples for the neural network. Work space of the robot is divided into two parts: global safe area and local dangerous area. In the global safe area, the robot only receives the attraction force from the target and it moves towards the target directly. In the dangerous area, except the attraction force, the robot also receives the repulsion force from the obstacle(s). The repulsion force and the angle between the obstacle and the target (origin of the coordinate is in the position of the robot) are used to be the inputs of the fuzzy inferencing system, and the deflection angle of the robot is the output. The final moving direction of the robot is determined by summing this deflection angle and the direction of the attraction force. The coordinates of the target and obstacle, and the moving direction of the robot corresponding to this position relationship, constitute the training samples for the neural network. Benefited from the precise moving direction obtained by the fuzzy artificial potential field algorithm, the neural network gets excellent path optimization ability. Simulation and physical experiment results demonstrate the potential of the proposed algorithm.

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Simple Global Path Planning Algorithm Using a Ray-Casting and Tracking Method

Cited by 7 publications

References 15 publications

Obstacle-avoiding intelligent algorithm for quad wheel robot path navigation

Obstacle-avoiding intelligent algorithm for quad wheel robot path navigation

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

Path planning of mobile robot in dynamic environment: fuzzy artificial potential field and extensible neural network

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