A Novel Approach to Localized a Robot in a Given Map with Optimization Using GP-GPU

Mittal, Rohit; Pathak, Vibhakar; Goyal, Shweta; Mithal, Amit

doi:10.1007/978-981-15-0426-6_17

Cited by 3 publications

(1 citation statement)

References 4 publications

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“…Also, there is a need to evaluate the motion stability of a robot on a diverse set of surfaces such as boulder tiles, marble flooring, glaze tiles, etc. Movements on such surfaces give an estimation of the frictional parameter between the tires of the robot and the surface [6,8,24]. For example, there is a possibility of collision of a losing structure on the surface, and disturbance in SEP.…”

Section: Related Workmentioning

confidence: 99%

Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments

Mittal,

Rani,

Pathak

et al. 2023

Computers

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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.

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Section: Related Workmentioning

confidence: 99%

Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments

Mittal,

Rani,

Pathak

et al. 2023

Computers

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Facial Recognition Model Using Custom Designed Deep Learning Architecture

Kesarwani,

Mittal,

Panwar

et al. 2024

Lecture Notes in Networks and Systems

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Building Climate Resilience Through AI-Enabled Education Strategies for Community Empowerment

Mittal,

Pathak,

Gaballa

2024

Practice, Progress, and Proficiency in Sustainability

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This chapter examines the effect of Artificial Intelligence (AI) on the education sector, focusing on its use and effects in executive structures, educational processes, and outcomes. The methodology involved an assessment of AI applications recognized through elementary examination. AI, along with human-like reasoning abilities, has significantly influenced training approaches in educational institutions. The study also investigates into the intersection of climate resilience and education, emphasizing AI's transformative potential in allowing communities to address rising climate change challenges. By leveraging AI-based educational strategies, communities can enhance their considerate of climate change impacts, adjust to changing conditions, and mitigate associated risks. The chapter aims how AI-enabled education can serve as a catalyst for community empowerment in building climate resilience. Through a detailed inspection of AI applications, the study aims to equip communities with the knowledge, skills, and tools necessary to thrive amidst a changing climate landscape.

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A Novel Approach to Localized a Robot in a Given Map with Optimization Using GP-GPU

Cited by 3 publications

References 4 publications

Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments

Low-Cost Multisensory Robot for Optimized Path Planning in Diverse Environments

Facial Recognition Model Using Custom Designed Deep Learning Architecture

Building Climate Resilience Through AI-Enabled Education Strategies for Community Empowerment

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