Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments
This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach work...
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MDPI AG
2024-10-01
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| Online Access: | https://www.mdpi.com/1424-8220/24/21/6986 |
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| author | Mangali Sravanthi Sravan Kumar Gunturi Mangali Chinna Chinnaiah Siew-Kei Lam G. Divya Vani Mudasar Basha Narambhatla Janardhan Dodde Hari Krishna Sanjay Dubey |
| author_facet | Mangali Sravanthi Sravan Kumar Gunturi Mangali Chinna Chinnaiah Siew-Kei Lam G. Divya Vani Mudasar Basha Narambhatla Janardhan Dodde Hari Krishna Sanjay Dubey |
| author_sort | Mangali Sravanthi |
| collection | DOAJ |
| description | This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach works on two levels: the estimation of human location and the robot’s intention to serve based on the human’s location at static and adaptive positions. This paper presents three methodologies to address these challenges: binary classification to analyze static and adaptive postures for human localization in indoor environments using the sensor fusion method, adaptive Simultaneous Localization and Mapping (SLAM) for the robot to deliver the task, and human–robot implicit communication. VLSI hardware schemes are developed for the proposed method. Initially, the control unit processes real-time sensor data through PIR sensors and multiple ultrasonic sensors to analyze the human posture. Subsequently, static and adaptive human posture data are communicated to the robot via Wi-Fi. Finally, the robot performs services for humans using an adaptive SLAM-based triangulation navigation method. The experimental validation was conducted in a hospital environment. The proposed algorithms were coded in Verilog HDL, simulated, and synthesized using VIVADO 2017.3. A Zed-board-based FPGA Xilinx board was used for experimental validation. |
| format | Article |
| id | doaj-art-247eb7eecb644e839f24a421188b6dd3 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj-art-247eb7eecb644e839f24a421188b6dd32025-08-20T02:14:16ZengMDPI AGSensors1424-82202024-10-012421698610.3390/s24216986Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor EnvironmentsMangali Sravanthi0Sravan Kumar Gunturi1Mangali Chinna Chinnaiah2Siew-Kei Lam3G. Divya Vani4Mudasar Basha5Narambhatla Janardhan6Dodde Hari Krishna7Sanjay Dubey8Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Aziznagar, Hyderabad 500075, Telangana, IndiaDepartment of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Aziznagar, Hyderabad 500075, Telangana, IndiaDepartment of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak, Narsapur 502313, Telangana, IndiaCollege of Computing and Data Science (CCDS), Nanyang Technological University, Singapore 639798, SingaporeDepartment of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak, Narsapur 502313, Telangana, IndiaDepartment of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak, Narsapur 502313, Telangana, IndiaDepartment of Mechanical Engineering, Chaitanya Bharati Institute of Technology, Gandipet, Hyderabad 500075, Telangana, IndiaDepartment of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak, Narsapur 502313, Telangana, IndiaDepartment of Electronics and Communications Engineering, B. V. Raju Institute of Technology, Medak, Narsapur 502313, Telangana, IndiaThis study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach works on two levels: the estimation of human location and the robot’s intention to serve based on the human’s location at static and adaptive positions. This paper presents three methodologies to address these challenges: binary classification to analyze static and adaptive postures for human localization in indoor environments using the sensor fusion method, adaptive Simultaneous Localization and Mapping (SLAM) for the robot to deliver the task, and human–robot implicit communication. VLSI hardware schemes are developed for the proposed method. Initially, the control unit processes real-time sensor data through PIR sensors and multiple ultrasonic sensors to analyze the human posture. Subsequently, static and adaptive human posture data are communicated to the robot via Wi-Fi. Finally, the robot performs services for humans using an adaptive SLAM-based triangulation navigation method. The experimental validation was conducted in a hospital environment. The proposed algorithms were coded in Verilog HDL, simulated, and synthesized using VIVADO 2017.3. A Zed-board-based FPGA Xilinx board was used for experimental validation.https://www.mdpi.com/1424-8220/24/21/6986posture recognitionlocalizationFPGAservice robotsensor fusion |
| spellingShingle | Mangali Sravanthi Sravan Kumar Gunturi Mangali Chinna Chinnaiah Siew-Kei Lam G. Divya Vani Mudasar Basha Narambhatla Janardhan Dodde Hari Krishna Sanjay Dubey Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments Sensors posture recognition localization FPGA service robot sensor fusion |
| title | Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments |
| title_full | Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments |
| title_fullStr | Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments |
| title_full_unstemmed | Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments |
| title_short | Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments |
| title_sort | adaptive fpga based accelerators for human robot interaction in indoor environments |
| topic | posture recognition localization FPGA service robot sensor fusion |
| url | https://www.mdpi.com/1424-8220/24/21/6986 |
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