Boundary Detection Robots
Hussein Safa1, Ahmad Taha Abdulsadda2, Ahmad Gahnam Wadday3
1Hussien Safa*, Communication department, Al najaf Technical engineering College, Al Furat Al Awast Technical University (ATU), Al najaf City, Iraq.
2Ahmad Taha Abdulsadda, Communication department, Al najaf Technical engineering College, Al Furat Al Awast Technical University(ATU), Al najaf City, Iraq.
3Ahmad Gahanam Wadday, Communication Department, Al Najaf Technical Engineering College, Al Furat Al Awast Technical University(ATU), Al najaf City, Iraq.
Manuscript received on February 01, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 952-955 | Volume-9 Issue-3, February, 2020. | Retrieval Number: B2655129219/2020©BEIESP | DOI: 10.35940/ijeat.C5399.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Mobile robot sensors have appeared as techniques for tracking the environment, search and rescue, exploration and mapping, civil infrastructure analysis, and military operations. Discovery and tracking of polluted areas with sensor mobile multi-robots is now regarded the solution to environmental and human safety issues. This paper shows some algorithms intended to allow mobile multi robots with sensor to estimate and monitor for polluted an irregular area in a synchronized way. Changes in the behavior of dangerous environmental boundaries, such as fire spreads or oil spills, provide appropriate data to mitigate the issue or even support evacuation actions to save human or animal life. In this paper, we present a model using a two-robot called it Boundary Detection Robot (BDR) moving around an environmental boundary to predict its shape through a continuous analytical function based on the combination of polynomial approximation. These robots are composed of many sensors each with embedded processors, wireless communication, and movement capabilities. We explain that when we increase the sample frequency and the robot velocity, the strategy converges to the exact boundary. We conducted experiments with simulated and actual robots to assess the estimation quality. We analyze the reliability of the control unit and other component in a robot simulator and assess the efficiency of the all components in a realistic set-up and environment model. We implement a stable transmission range of robot control laws with sensors to track irregular area boundaries.
Keywords: Boundary detection, Environmental monitoring, robotics, control theory .