# A Framework for Bluetooth-Based Real-Time Audio Data Acquisition in Mobile Robotics
## 1 Introduction  
The rapid expansion of microcontroller platforms, such as ESP32, Arduino, and Raspberry Pi, has resulted in a significant increase in the capabilities of mobile robotics, while simultaneously reducing the associated costs. These platforms have allowed developers to build increasingly sophisticated interactive systems capable of navigating physical spaces while also collecting data about their environments. Although vision-based sensing is the mainstay of mobile robotics, environmental audio capture is an under-exploited modality that can provide rich contextual information not available to other sensing modes [1, 2]. However, when implementing audio sampling on resource-limited mobile robots, several unique challenges emerge that stationary solutions never encounter. On mobileplatforms, work must be conducted within limited power budgets, constrained computational resources, noise potentially from onboard motors or actuators, and the necessity to provide timely feedback control signals without compromising the integrity of the audio stream [3; 4]. These challenges become even more pronounced when aiming to communicate audio data wirelessly whilst keeping native positioning inputs responsive to the robot's movements. Bluetooth technology represents an attractive communication standard for such applications due to its ubiquity, relatively low power consumption, and adequate data rates for many embedded applications [5; 6]. However, as noted by several researchers [7; 8], Bluetooth presents intrinsic challenges when employed for concurrent real-time control and streaming applications: limited bandwidth, susceptibility to packet loss, and variable latency that can impair both control precision and audio fidelity. Recent developments in wireless technologies for flexible and wearable sensing have addressed some of these challenges [9], but applications in mobile robotics remain limited. This paper introduces a novel framework that addresses these challenges by synthesizing a unified approach to real-time audio acquisition, motor control, and data transmission. This study proposes a dual-thread architecture that effectively partitions time-sensitive motor commands from bandwidth-intensive audio data, while maintaining synchronized operation through a carefully optimized Bluetooth communication protocol. By leveraging the I2S (Inter-IC Sound) digital audio interface coupled with dynamic range compression techniques, this approach achieves high-quality audio capture that coexists harmoniously with precise motor control. This approach builds upon existing research in networking architectures and protocols for IoT applications [10] while extending them to the specific requirements of mobile acoustic sensing. The framework integrates acoustic sensing with motion in resource-limited robots, uncovering wholly new application spaces. As depicted in Figure 1, this architecture consists of a digital MEMS microphone connected to the GPIO via I2S, a Bluetooth communication layer allowing for bidirectional data exchange, and a motor control mechanism allowing the platform to move and capture acoustic data. This approach is one major advancement over the existing literature, which has traditionally treated audio capture and mobility as mutually exclusive requirements. The integrated power management, appropriate handling of input buffers, adaptive buffer  
Figure 1: System architecture with data flow. sizing, and dynamic bit-depth adjustment demonstrate that robotic platforms can serve as quality acoustic sensors while still being able to facilitate effective locomotion and maintain responsive control over their movements.