Different Kinematic Path Following Controllers for a Wheeled Mobile Robot of (2,0) Type

Płaskonka, J.

doi:10.1007/s10846-013-9879-6

Cited by 24 publications

(15 citation statements)

References 16 publications

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“…In Proceedings of the 9th IEEE Mediterranean Conference on Control and Automation, IEEE, Dubrovnik, Croatia, pp. [1][2][3][4][5][6]2001. A. P. Aguiar, J. P. Hespanha.…”

Section: Open Accessmentioning

confidence: 99%

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A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Panda

Subudhi

Pati

2020

Int. J. Autom. Comput.

148

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The underwater path planning problem deals with finding an optimal or sub-optimal route between an origin point and a termination point in marine environments. The underwater environment is still considered as a great challenge for the path planning of autonomous underwater vehicles (AUVs) because of its hostile and dynamic nature. The major constraints for path planning are limited data transmission capability, power and sensing technology available for underwater operations. The sea environment is subjected to a large set of challenging factors classified as atmospheric, coastal and gravitational. Based on whether the impact of these factors can be approximated or not, the underwater environment can be characterized as predictable and unpredictable respectively. The classical path planning algorithms based on artificial intelligence assume that environmental conditions are known apriori to the path planner. But the current path planning algorithms involve continual interaction with the environment considering the environment as dynamic and its effect cannot be predicted. Path planning is necessary for many applications involving AUVs. These are based upon planning safety routes with minimum energy cost and computation overheads. This review is intended to summarize various path planning strategies for AUVs on the basis of characterization of underwater environments as predictable and unpredictable. The algorithms employed in path planning of single AUV and multiple AUVs are reviewed in the light of predictable and unpredictable environments.

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“…In Proceedings of the 9th IEEE Mediterranean Conference on Control and Automation, IEEE, Dubrovnik, Croatia, pp. [1][2][3][4][5][6]2001. A. P. Aguiar, J. P. Hespanha.…”

Section: Open Accessmentioning

confidence: 99%

“…In the path planning control (PPC) problem, an AUV has to traverse a convergent path without temporal constraints [5] . Earlier works on PPC of wheeled robots solved two major issues reported as "path parameterization" and the selection of the termination point on the path [6] .…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Panda

Subudhi

Pati

2020

Int. J. Autom. Comput.

148

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“…and carrying out the similar reasoning to one which was presented in the subsection 4.1. The complete proof of the convergence can be found in (Płaskonka, 2013).…”

Section: Non-singular Control Algorithmmentioning

confidence: 99%

Singular and Non-singular Path Following Control of a Wheeled Mobile Robot of (2,0) Type

Płaskonka

2013

Proceedings of the 10th International Conference on Informatics in Control, Automation and Robotics

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This paper relates to the problem of a path following task for a wheeled mobile platform of (2,0) type. Two kinematic control algorithms, Micaelli-Samson algorithm and Soetanto-Lapierre-Pascoal algorithm, which are based on either the Serret-Frenet frame with an orthogonal projection or the Serret-Frenet frame with a nonorthogonal projection of a robot on the desired path, were presented. The additional condition that should be imposed on the function δ, which is a parameter depending on a linear velocity of the robot and on a distance error, was described. The influence of the function δ on the convergence of the non-singular algorithm has been shown using computer simulations.

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“…Fundamentals of control algorithm employed in this paper have been given by Braitenberg [2], the Braitenberg algorithm has been also discussed in [4]. The broad study about models of mobile robots has been given in [9].…”

Section: Introductionmentioning

confidence: 99%

The agent, state-space model of the mobile robot

Oprzędkiewicz¹,

Ciurej²,

Garbacz³

2018

PAR

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Different Kinematic Path Following Controllers for a Wheeled Mobile Robot of (2,0) Type

Cited by 24 publications

References 16 publications

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

A Comprehensive Review of Path Planning Algorithms for Autonomous Underwater Vehicles

Singular and Non-singular Path Following Control of a Wheeled Mobile Robot of (2,0) Type

The agent, state-space model of the mobile robot

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