The efficient operation and diverse service capabilities of commercial service robots are rooted in their precisely integrated structural design. As a complex system integrating mechanical engineering, electronic technology, and intelligent algorithms, its structure can be divided into four core modules: the execution layer, the perception layer, the control layer, and the interaction layer. These layers work collaboratively to achieve comprehensive functions including environmental adaptation, task execution, and intelligent interaction.
The execution layer is the "muscle" of the robot's physical movements, mainly composed of a mobile chassis and functional actuators. The mobile chassis often adopts a wheeled or tracked design, equipped with servo motors, reducers, and suspension systems to ensure stable movement on flat ground or slightly complex terrain. Some high-end models also integrate omnidirectional wheels to improve steering flexibility. The functional actuators vary depending on the application scenario: delivery robots are equipped with liftable cargo compartments and anti-shake pallets to ensure the safety of goods transportation; cleaning robots are equipped with rotating brushes and negative pressure vacuum modules to achieve efficient floor cleaning; reception robots may integrate robotic arms for delivering lightweight items, and their joint degrees of freedom and torque control precision directly affect operational reliability.
The perception layer acts as the robot's "sensors" for understanding its environment, composed of arrays of various sensors. LiDAR (Light Detection and Ranging) constructs high-precision point cloud maps by emitting laser pulses, serving as the core for centimeter-level positioning and obstacle avoidance. Visual sensors (such as RGB-D cameras and panoramic cameras) are responsible for recognizing obstacle outlines and reading signage information (such as QR codes and text guidance). Inertial Measurement Units (IMUs) and ultrasonic sensors assist in compensating for positioning drift in dynamic environments, playing a supplementary role, especially in low-light or texture-deficient scenarios. Multi-sensor data fusion algorithms enable the robot to build a 3D environment model in real time and predict potential risks.
The control layer is the robot's "nerve center," centered on an embedded controller or industrial-grade computing platform, and equipped with a real-time operating system (RTOS) and motion control algorithms. After receiving environmental data from the perception layer, it generates the optimal movement trajectory using path planning algorithms (such as A* and DWA) and sends commands to the execution layer to adjust motor speeds and servo angles. Simultaneously, the control layer coordinates the power consumption of various modules, balancing performance and battery life requirements. Some models also support remote OTA (Over-The-Air) upgrades to optimize control logic.
The interaction layer serves as a "bridge" for the robot to communicate with the outside world, encompassing a voice acquisition and playback module, a touchscreen display, and indicator lights. A microphone array, combined with noise reduction algorithms, enables far-field voice wake-up and sound source localization, while the speaker outputs natural voice feedback. The touchscreen supports a graphical interface, catering to the interactive habits of users of different ages. Indicator lights convey status information (such as battery level and fault warnings) through color and flashing frequency, forming a multi-dimensional and intuitive communication.
The structural design of commercial service robots always revolves around "scenario adaptability" and "reliability." From the chassis's load capacity to the redundant configuration of sensors, from the real-time performance of control algorithms to the ease of use of the interaction module, every detail must consider both technical feasibility and practical operational needs. With advancements in lightweight materials, modular design, and edge computing technology, their structure is evolving towards greater compactness and intelligence, providing more robust hardware support for stable services in complex scenarios.
