Architecture of the Vision System of a Line Following Mobile Robot Operating in Static Environment

Rahman, Mahbubur; Haque, Abul L.; Islam, Mashnoon

doi:10.1109/inmic.2005.334473

Cited by 9 publications

(2 citation statements)

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“…However, if there are pixels denoting a straight line towards the periphery of the image the system will fail to predict accurate control outputs. Similarly, Rahman et al propose a line following vision system assuming that objects in the environment are static [8]. Although this approach may work in constrained environments, the expectation of a static environment contradicts most real world scenarios.…”

Section: Related Workmentioning

confidence: 99%

Camera-Based Adaptive Trajectory Guidance via Neural Networks

Rajguru

Collander

Beksi

2020

2020 6th International Conference on Mechatronics and Robotics Engineering (ICMRE)

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In this paper, we introduce a novel method to capture visual trajectories for navigating an indoor robot in dynamic settings using streaming image data. First, an image processing pipeline is proposed to accurately segment trajectories from noisy backgrounds. Next, the captured trajectories are used to design, train, and compare two neural network architectures for predicting acceleration and steering commands for a line following robot over a continuous space in real time. Lastly, experimental results demonstrate the performance of the neural networks versus human teleoperation of the robot and the viability of the system in environments with occlusions and/or low-light conditions.

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Section: Related Workmentioning

confidence: 99%

Camera-Based Adaptive Trajectory Guidance via Neural Networks

Rajguru

Collander

Beksi

2020

2020 6th International Conference on Mechatronics and Robotics Engineering (ICMRE)

View full text Add to dashboard Cite

show abstract

“…The smoothness of the robot's motion is also dependent on the spacing between the cells forming the line sensor. A significant disadvantage of such optical systems is relatively low resolution of the tracking system, which can be increases using some other vision based systems with wide possibilities of analysing data acquired from the front Dupuis & Parizeau (2006); Rahman et al (2005). Nevertheless the analysis of the full acquired image even with low resolution is usually computationally demanding and time consuming, especially in the presence of some obstacles, some line intersections etc., assuming also varying lighting conditions.…”

Section: Application For the Line Following Robotsmentioning

confidence: 99%