Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments
The automation industry faces the challenge of avoiding interference with obstacles, estimating the next move of a robot, and optimizing its path in various environments. Although researchers have predicted the next move of a robot in linear and non-linear environments, there is a lack of precise es...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-12-01
|
| Series: | Computers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-431X/12/12/250 |
| _version_ | 1797381513533194240 |
|---|---|
| author | Rohit Mittal Geeta Rani Vibhakar Pathak Sonam Chhikara Vijaypal Singh Dhaka Eugenio Vocaturo Ester Zumpano |
| author_facet | Rohit Mittal Geeta Rani Vibhakar Pathak Sonam Chhikara Vijaypal Singh Dhaka Eugenio Vocaturo Ester Zumpano |
| author_sort | Rohit Mittal |
| collection | DOAJ |
| description | The automation industry faces the challenge of avoiding interference with obstacles, estimating the next move of a robot, and optimizing its path in various environments. Although researchers have predicted the next move of a robot in linear and non-linear environments, there is a lack of precise estimation of sectorial error probability while moving a robot on a curvy path. Additionally, existing approaches use visual sensors, incur high costs for robot design, and ineffective in achieving motion stability on various surfaces. To address these issues, the authors in this manuscript propose a low-cost and multisensory robot capable of moving on an optimized path in diverse environments with eight degrees of freedom. The authors use the extended Kalman filter and unscented Kalman filter for localization and position estimation of the robot. They also compare the sectorial path prediction error at different angles from 0° to 180° and demonstrate the mathematical modeling of various operations involved in navigating the robot. The minimum deviation of 1.125 cm between the actual and predicted path proves the effectiveness of the robot in a real-life environment. |
| first_indexed | 2024-03-08T20:52:40Z |
| format | Article |
| id | doaj.art-5ae27313f99c4ee184ad7de1cf5780d7 |
| institution | Directory Open Access Journal |
| issn | 2073-431X |
| language | English |
| last_indexed | 2024-03-08T20:52:40Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computers |
| spelling | doaj.art-5ae27313f99c4ee184ad7de1cf5780d72023-12-22T14:01:23ZengMDPI AGComputers2073-431X2023-12-01121225010.3390/computers12120250Low-Cost Multisensory Robot for Optimized Path Planning in Diverse EnvironmentsRohit Mittal0Geeta Rani1Vibhakar Pathak2Sonam Chhikara3Vijaypal Singh Dhaka4Eugenio Vocaturo5Ester Zumpano6Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, IndiaComputer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, IndiaDepartment of Information Technology, Arya College of Engineering and Information Technology, Jaipur 302028, IndiaComputer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, IndiaComputer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, IndiaDepartment of Computer Engineering, Modeling, Electronics and Systems, University of Calabria, 87036 Rende, Cosenza, ItalyDepartment of Computer Engineering, Modeling, Electronics and Systems, University of Calabria, 87036 Rende, Cosenza, ItalyThe automation industry faces the challenge of avoiding interference with obstacles, estimating the next move of a robot, and optimizing its path in various environments. Although researchers have predicted the next move of a robot in linear and non-linear environments, there is a lack of precise estimation of sectorial error probability while moving a robot on a curvy path. Additionally, existing approaches use visual sensors, incur high costs for robot design, and ineffective in achieving motion stability on various surfaces. To address these issues, the authors in this manuscript propose a low-cost and multisensory robot capable of moving on an optimized path in diverse environments with eight degrees of freedom. The authors use the extended Kalman filter and unscented Kalman filter for localization and position estimation of the robot. They also compare the sectorial path prediction error at different angles from 0° to 180° and demonstrate the mathematical modeling of various operations involved in navigating the robot. The minimum deviation of 1.125 cm between the actual and predicted path proves the effectiveness of the robot in a real-life environment.https://www.mdpi.com/2073-431X/12/12/250sectorial errormulti-sensoroptimizerobotKalman filter |
| spellingShingle | Rohit Mittal Geeta Rani Vibhakar Pathak Sonam Chhikara Vijaypal Singh Dhaka Eugenio Vocaturo Ester Zumpano Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments Computers sectorial error multi-sensor optimize robot Kalman filter |
| title | Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments |
| title_full | Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments |
| title_fullStr | Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments |
| title_full_unstemmed | Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments |
| title_short | Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments |
| title_sort | low cost multisensory robot for optimized path planning in diverse environments |
| topic | sectorial error multi-sensor optimize robot Kalman filter |
| url | https://www.mdpi.com/2073-431X/12/12/250 |
| work_keys_str_mv | AT rohitmittal lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT geetarani lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT vibhakarpathak lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT sonamchhikara lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT vijaypalsinghdhaka lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT eugeniovocaturo lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments AT esterzumpano lowcostmultisensoryrobotforoptimizedpathplanningindiverseenvironments |