On‐line path planning strategy integrated with collision and dead‐lock avoidance schemes for wheeled mobile robot in indoor environments

2008 ◽  
Vol 35 (5) ◽  
pp. 421-434 ◽  
Author(s):  
Ya‐Chun Chang ◽  
Yoshio Yamamoto
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Indoor Environments ◽  
Planning Strategy ◽  
On Line ◽  
Line Path

Investigating Reduced Path Planning Strategy for Differential Wheeled Mobile Robot

Robotica ◽  
2019 ◽  
Vol 38 (2) ◽  
pp. 235-255 ◽  
Author(s):  
Raouf Fareh ◽  
Mohammed Baziyad ◽  
Mohammad H. Rahman ◽  
Tamer Rabie ◽  
Maamar Bettayeb
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Control Strategy ◽  
Wheeled Mobile Robot ◽  
Computational Time ◽  
Planning Strategy ◽  
Starting Point ◽  
Planning Algorithm ◽  
Path Efficiency ◽  
Path Planning Algorithm

SummaryThis paper presents a vision-based path planning strategy that aims to reduce the computational time required by a robot to find a feasible path from a starting point to the goal point. The proposed algorithm presents a novel strategy that can be implemented on any well-known path planning algorithm such as A*, D* and probabilistic roadmap (PRM), to improve the swiftness of these algorithms. This path planning algorithm is suitable for real-time scenarios since it reduces the computational time compared to the basis and traditional algorithms. To test the proposed path planning strategy, a tracking control strategy is implemented on a mobile platform. This control strategy consists of three major stages. The first stage deals with gathering information about the surrounding environment using vision techniques. In the second stage, a free-obstacle path is generated using the proposed reduced scheme. In the final stage, a Lyapunov kinematic tracking controller and two Artificial Neural Network (ANN) based-controllers are implemented to track the proposed path by adjusting the rotational and linear velocity of the robot. The proposed path planning strategy is tested on a Pioneer P3-DX differential wheeled mobile robot and an Xtion PRO depth camera. Experimental results prove the efficiency of the proposed path planning scheme, which was able to reduce the computational time by a large percentage which reached up to 88% of the time needed by the basis and traditional scheme, without significant adverse effect on the workability of the basis algorithm. Moreover, the proposed path planning algorithm has improved the path efficiency, in terms of the path length and trackability, challenging the traditional trade-off between swiftness and path efficiency.

Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation

2011 ◽  
Vol 37 (6) ◽  
pp. 1058-1070 ◽  
Author(s):  
Jagadish Chandra Mohanta ◽  
Dayal Ramakrushna Parhi ◽  
Saroj Kumar Patel
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Robot Navigation ◽  
Mobile Robot Navigation ◽  
Autonomous Mobile Robot ◽  
Planning Strategy

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

2018 ◽  
Vol 45 (5) ◽  
pp. 688-702 ◽  
Author(s):  
Dayal R. Parhi ◽  
Animesh Chhotray
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Wheeled Mobile Robot ◽  
Weight Functions ◽  
Feasible Point ◽  
Content Type ◽  
Intelligent Technique ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Incremental Step

PurposeThis paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR).Design/methodology/approachThis 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.FindingsAuthenticity 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 implicationsThis 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/valueA 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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