Vision-Based Robot Following Using PID Control

Pati, Chandra Sekhar; Kala, Rahul

doi:10.3390/technologies5020034

Cited by 14 publications

(7 citation statements)

References 6 publications

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“…The system error vector is chosen as the quantifiable values that can be recovered using a motion estimation approach, taking into account the model uncertainty [15]. Pati and Kala developed and tuned a PID controller for a mobile robot, emphasizing its significance in achieving accurate and robust robot control with vision [16]. Rubio et al provided a comprehensive overview of mobile robots, exploring various techniques of planning and mapping their paths using perception [17].…”

Section: Related Workmentioning

confidence: 99%

Dual Mode PID Controller for Path Planning of Encoder Less Mobile Robots in Warehouse Environment

Karthik,

Menaka,

Kishore

et al. 2024

IEEE Access

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Mobile robots have emerged as versatile substitutes for human labor across diverse domains, offering promising applications in surveillance, healthcare, and beyond. Fundamental to their autonomy are the core capabilities of movement, perception, cognition, and navigation. This research introduces a novel approach known as the Dual PID based low-cost navigation system (DPLNS), designed specifically for indoor warehouse-like environments. The primary objective of this technique is to enable seamless point-to-point traversal. This is achieved through a fusion of gyroscope correction and visual PID control mechanisms. Leveraging a strategically positioned eagle-eye perspective camera, the system gained crucial insights for navigation. To ensure the uninterrupted execution of planned trajectories, the system employs the Message Queuing Telemetry Transport (MQTT) protocol. This technology ensures smooth communication and coordination of actions. The experimental validation of the proposed strategy highlights its efficacy, positioning it as a promising solution for modern warehouse automation needs. By advancing the capabilities of mobile robots within warehouse contexts, this research not only addresses immediate operational demands, but also paves the way for broader applications across various other fields. The developed system enables robust detection and successful path traversal to the designated spot through a position control operating at average of 12.3 rad/s.

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Section: Related Workmentioning

confidence: 99%

Dual Mode PID Controller for Path Planning of Encoder Less Mobile Robots in Warehouse Environment

Karthik,

Menaka,

Kishore

et al. 2024

IEEE Access

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show abstract

“…There are several studies on this subject. Pati and Kala [26] presented robot following based on computer and PID control for a different wheel robots. They designed two robots.…”

Section: Non-chattering Sliding Mode Controller Designmentioning

confidence: 99%

Sliding mode control of a line following robot

Yıldız

Can

Özgüney

et al. 2020

J Braz. Soc. Mech. Sci. Eng.

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Line following robots have ability to track a given path autonomously using feedback mechanisms. The path is usually a black line on a white surface or a white line on a black surface. Today, line following robots are used in medical, industrial and automotive industries. Therefore, the studies on the line following robots have been increased recently. In this study, a robust, non-chattering sliding mode control (SMC) is designed and applied for a line following robot. The mobile robot is designed to sense the straight or curved path with its infrared sensors mounted on the robot. Therefore, these infrared sensors provide continuous streaming of the defined path to guide or direct changes in robot by activating motors on right wheel or/ and left wheel. The control strategy is curial to track complex paths accurately and to have a fast, stable and accurate line following robot. Thus, for comparison, conventional proportional-integral-derivative (PID) is also applied to robot. The main purpose of this study is to investigate performance of sliding mode control during path tracking. For this, numerical solution and experimental study were carried out. From the results, it was understood that sliding mode controller is highly efficient in tracking the path.

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“…The paper also presents its results on simulation and real-time runs. Pati and Kala [15] made a small mobile robot called a slave that follows a bigger mobile robot called a master. The master robot was remotely operated.…”

Section: Literature Surveymentioning

confidence: 99%

Motion Planning for a Chain of Mobile Robots Using A* and Potential Field

2018

Self Cite

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Traditionally, motion planning involved navigating one robot from source to goal for accomplishing a task. Now, tasks mostly require movement of a team of robots to the goal site, requiring a chain of robots to reach the desired goal. While numerous efforts are made in the literature for solving the problems of motion planning of a single robot and collective robot navigation in isolation, this paper fuses the two paradigms to let a chain of robot navigate. Further, this paper uses SLAM to first make a static map using a high-end robot, over which the physical low-sensing robots run. Deliberative Planning uses A* algorithm to plan the path. Reactive planning uses the Potential Field Approach to avoid obstacles and stay as close to the initial path planned as possible. These two algorithms are then merged to provide an algorithm that allows the robot to reach its goal via the shortest path possible while avoiding obstacles. The algorithm is further extended to multiple robots so that one robot is followed by the next robot and so on, thus forming a chain. In order to maintain the robots in a chain form, the Elastic Strip model is used. The algorithm proposed successfully executes the above stated when tested on Amigobot robots in an office environment using a map made by the Pioneer LX robot. The proposed algorithm works well for moving a group of robots in a chain in a mapped environment.

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Vision-Based Robot Following Using PID Control

Cited by 14 publications

References 6 publications

Dual Mode PID Controller for Path Planning of Encoder Less Mobile Robots in Warehouse Environment

Dual Mode PID Controller for Path Planning of Encoder Less Mobile Robots in Warehouse Environment

Sliding mode control of a line following robot

Motion Planning for a Chain of Mobile Robots Using A* and Potential Field

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