# A Framework for Bluetooth-Based Real-Time Audio Data Acquisition in Mobile Robotics
## 2 Literature Review
[21] presented a multimodal dataset for multi-robot activity recognition leveraging Wi-Fi sensing, video, and audio, which are very useful sources for the development and assessment of multi-sensor robotic systems. The integration of voice control with robotic platforms has been explored by several researchers. [PERSON] et al. [22] designed and implemented voice command recognition and sound source localization systems for human-robot interactions. [PERSON] et al. [23] developed remote and voice-controlled surveillance robots with multimodal operation, while [PERSON] et al. [24] created voice-controlled robotic cars, demonstrating the practical applications of audio processing in mobile robotics. [PERSON] et al. [25] advanced this field with the development of optical laser microphones for human-robot interactions, enabling speech recognition in extremely noisy service environments. In the area of autonomous robotic systems with audio capabilities, [PERSON] and [PERSON] [26] developed IoT-based smart security robots with Android apps, night vision, and enhanced threat detection. [PERSON] et al. [27] created solar-powered autonomous robotic cars for surveillance, while [PERSON] and [PERSON] [28] designed AI-based voice-controlled humanoid robots. [PERSON] et al. [29] implemented alive human detection and health monitoring using IoT-based robots, highlighting the growing interest in combining mobility with audio sensing for practical applications. [PERSON] et al. [30] further contributed to this area with research on fuzzy-guided autonomous nursing robots using wireless beacon networks. The challenges of navigation and control in mobile robots have been addressed by [PERSON] et al. [31], who developed autonomous navigation and steering control based on wireless non-wheeled snake robots. [PERSON] et al. [32] proposed multi-robot movement based on a new modified source-seeking algorithm, while [PERSON] and [PERSON] [33] focused on the trajectory planning and control of multiple mobile robots using hybrid controllers. More specialized approaches were explored by [PERSON] et al. [34], who investigated the human-like motion planning of robotic arms based on human arm motion patterns, and by [PERSON] et al. [35], who conducted experimental evaluations of instrumented bio-inspired cable-driven compliant continuum robots. Recent work by [PERSON] et al. [36] explored robot sound design through design thinking, addressing the acoustic aspects of human-robot interactions. [PERSON] et al. [37] developed an intellectual design for bomb identification and defusing robots based on logical gesturing mechanisms, demonstrating advanced applications in security robotics. Meanwhile, [PERSON] et al. [38] presented research on efficient approaches to unsupervised instance matching with applications to linked data, offering potential methodologies for processing and analyzing the data collected by mobile sensing platforms. Despite these advancements, a significant gap exists in the literature regarding integrated frameworks that effectively manage both movement control and audio capture on resource-constrained robotic platforms. Most existing solutions address these as separate challenges, resulting in systems that either compromise mobility for audio quality or sacrifice acoustic sensing for movement capability. This research addresses this gap by proposing a unified framework that optimizes both aspects simultaneously through careful hardware integration and innovative software architecture.