Obstacle Avoidance for Trajectory Tracking Control of Wheeled Mobile Robots

Șolea, Răzvan; Cernega, Daniela

doi:10.3182/20120523-3-ro-2023.00308

Cited by 7 publications

(6 citation statements)

References 13 publications

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“…The implementation of SMC strategy for instance is easy and fast with respect to response time. It also performs well in a condition with uncertain and unconducive external factors [64]. Also, these methods can combine well with other methods and they perform better when blended with other methods.…”

Section: Strengths Of Conventional Path Planning Methodsmentioning

confidence: 91%

“…In a different development, sliding mode control (SMC) was considered by some researchers [62][63][64]. SMC is a nonlinear control method that brings about changes in the dynamics of a nonlinear system by applying discontinuous control signal that force the system to slide towards a cross section of the normal behavior of the system.…”

Section: Sliding Mode Control Path Planning Methodmentioning

confidence: 99%

“…Besides, SMC methods are fast with respect to response time and are also good transient robust when it comes to uncertain systems and other external factors that are not conducive [64]. But, it does not perform well if the longitudinal velocity of the robot is fast.…”

Section: Challenges Of Conventional Path Planning Methodsmentioning

confidence: 99%

See 2 more Smart Citations

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

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Safe and smooth mobile robot navigation through cluttered environment from the initial position to goal with optimal path is required to achieve intelligent autonomous ground vehicles. There are countless research contributions from researchers aiming at finding solution to autonomous mobile robot path planning problems. This paper presents an overview of nature-inspired, conventional, and hybrid path planning strategies employed by researchers over the years for mobile robot path planning problem. The main strengths and challenges of path planning methods employed by researchers were identified and discussed. Future directions for path planning research is given. The results of this paper can significantly enhance how effective path planning methods could be employed and implemented to achieve real-time intelligent autonomous ground vehicles.

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Section: Strengths Of Conventional Path Planning Methodsmentioning

confidence: 91%

Section: Sliding Mode Control Path Planning Methodmentioning

confidence: 99%

See 1 more Smart Citation

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

Ayawli

Chellali

Appiah

et al. 2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…SMC is a non-linear control algorithm, considered as effective approach and solution due to its easy implementation, robustness in parameters variation, fast dynamic response, and good tracking ability. In a different development, SMC was considered by some researchers [39,40]. The algorithm works when a discontinuous signal applied to a control signal of system to command it and slide it to prescribed path.…”

Section: Sliding Mode Controlmentioning

confidence: 99%

A Review of Control Algorithm for Autonomous Guided Vehicle

Gul

2020

IJEECS

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The autonomous guided vehicle is a efficient and effective platform for control system. Their non-linear nature helps in analysing the control algorithms more efficiently and effectively. The main objective of path planning is to find the optimal and shortest path avoiding the time complexity so environment can be modelled completely for vehicle. The paper includes explanation of different systems together with numerous algorithms have been discussed with advantages and disadvantages for example: Fuzzy control, Neural Control, Back-stepping control, Adaptive control, Sliding mode control and PID control and linear quadratic regulator. The conclusion includes the hybrid system integration based on the advantages and disadvantages presented in this paper.

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“…Classical methods such as PF, DWA, A*, and PRM path planning are easy to implement, perform better when blended with other methods, fast with respect to response time. 13,14 However, such conventional methods are computationally expensive and typically rely on accuracy of cameras and sensors to collect data from the environment; making measurement uncertain when noise are inherent. 15 For example, a heuristic A-Star and dynamic steering algorithms use predefined grid-based environment map to find the shortest path based on information received from sonar sensor.…”

Section: Related Workmentioning

confidence: 99%

Fenceless obstacle avoidance method for efficient and safe human–robot collaboration in a shared work space

Mayyas

Vadlamudi

Syed

2020

International Journal of Advanced Robotic Systems

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In a given manufacturing setting where workers or robots are coexisting in a confined area and their movements are not coordinated due to loss in communication or because they are freely ranging relative to each other, the development of an onboard safeguard system for a robot becomes a necessity to reduce accidents while the production efficiency is uncompromised. This article develops a two-dimensional dynamics model that predicts the relative position between a robot’s end-of-arm tooling and an approaching object or threat. The safety strategy applied to the robot is derived from the calculation of three parameters: the time of collision predicted from the linear motion between the approaching object and the robot’s end-of-arm tooling, the relative absolute distance, and the overlapping area ratio. These parameters combined are updated in a cost function that is sufficiently alarming the collision severity of an approaching object in real time. This model enables deployment a safe and a productive collaborative interaction in the manufacturing environment where workers and robots are seemingly moving in close proximity within an open workspace with less safeguard barriers.

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Obstacle Avoidance for Trajectory Tracking Control of Wheeled Mobile Robots

Cited by 7 publications

References 13 publications

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning

A Review of Control Algorithm for Autonomous Guided Vehicle

Fenceless obstacle avoidance method for efficient and safe human–robot collaboration in a shared work space

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