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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63636
Volume:
10 |
5 |
May 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Robotics and Automation Engineering
Zeal College of Engineering and Research, Pune
Autonomous Mobile Robots (AMRs) are becoming increasingly important in modern automation systems, especially in applications such as warehouses, healthcare, and smart environments. Traditional robot control methods often rely on manual interfaces such as keyboards, joysticks, or mobile applications, which may not always be convenient or accessible. Voice-based control provides a more natural and user-friendly way for humans to interact with robotic systems. This research focuses on the development of a Voice Controlled Autonomous Mobile Robot using ROS2 and the VOSK Speech-to-Text module. The proposed system allows the robot to receive voice commands from the user, convert speech into text using the VOSK engine, and process the commands through ROS2 nodes to control the robot’s movement. The robot can interpret commands such as forward, backward, left, right, and stop, enabling intuitive human–robot interaction. ROS2 provides a flexible and scalable framework for communication between different modules of the robot, while VOSK enables offline and real-time speech recognition. The aim of this work is to create a reliable and efficient voice-controlled robotic system that improves usability and supports autonomous navigation in indoor environments.
KEYWORDS
This paper Presents Task driven Approach For the autonomous Navigation That uses Lidar technology, SLAM technology ,Speech to text module for communication and ROS2 Framework As operating system to achieve Autonomous navigation. The robot is capable of autonomous navigation We made an autonomous robot that uses SLAM for navigation and a microphone that turns speech into text for control. The robot was able to move around and follow simple voice commands. This project taught us how combining mapping and voice systems can make robots more useful. Even though it is not perfect, it shows that such systems can be applied in real life.
1) T. Dong, X. Song, Y. Zhang, X. Qin, Y. Liu, and Z. Bai, "ViT-Enabled Task-Driven Autonomous Heuristic Navigation Based on Deep Reinforcement Learning," IEEE Robotics and Automation Letters, 2025. (p. 1) 2) Van Manh Tran and Gon-Woo Kim, "Cooperative Deep Reinforcement Learning Policies for Autonomous Navigation in Complex Environments," IEEE Access, 2024. 3) A Eirale, M. Martini, and M. Chiaberge, "Human Following and Guidance by Autonomous Mobile Robots: A Comprehensive Review," IEEE Access, 2025. (p. 1) 4) S. Gummadi, M. V. Gasparino, D. Vasisht, and G. Chowdhary, "Fed-EC: Bandwidth-Efficient Clustering-Based Federated Learning for Autonomous Visual Robot Navigation," IEEE Robotics and Automation Letters, 2024 (p. 1) 5) N. Rohini, S. U. Begum, P. Chikkavarapu, B. Prathyusha, and S. Munaganooru, "Design and Implementation of an Intelligent Voice Controlled Mobile Robot," International Journal for Research Trends and Innovation, 2022 (p. 1) 6) K. Kainth, M. B. Siddiqui, H. G. S. Pal, and R. Faujdar, "Voice controlled robotic vehicle," International Journal of Computing and Artificial Intelligence, 2024 (p. 1). 7) S. Sachdeva, J. Macwan, C. Patel, and N. Doshi, "Voice-Controlled Autonomous Vehicle Using IoT," Procedia Computer Science, 2019 (p. 1). 8) H. Rashid, I. U. Ahmed, S. B. Osman, Q. Newaz, M. Rasheduzzaman, and S. M. T. Reza, "Design and Implementation of a Voice Controlled Robot with Human Interaction Ability," International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2), 2017 (p. 2). 9) S. A. Rafiq et al., "Design of Autonomous Rover for Firefighter Rescue: Integrating Deep Learning with ROS2," 2024 IEEE World AI IoT Congress (AIIoT), 2024 (p. 1). 10) Weijie Ye, Junli Gao, Huajun Chen, Jing Guo, A Voice Control Platform of Mobile Robot through ROS, Conference Paper (ChiCC), 2019.
Publication Date
5/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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