Below is a comprehensive analysis of the advantages and disadvantages of x86, RK (Rockchip), and NV (NVIDIA) platforms in AGV/AMR robot controller solutions:

I. Core Performance Comparison

Platform

Advantages

Limitations

Applicable Scenarios

‌x86‌

Multi-core high-frequency CPUs support complex algorithm computations, suitable for large-scale path planning and multi-robot collaborative control.
Strong compatibility, can run Windows/Linux systems, facilitating industrial software integration.
Higher power consumption (15-45W), affecting mobile device battery life.
Hardware cost is higher than embedded solutions.

AMR clusters with high-precision navigation, complex scenarios requiring real-time data processing.

‌RK‌

Low power consumption (5-10W) design, suitable for long-duration basic AGV material handling tasks.
High integration, supports multi-interface expansion (CAN/USB/GPIO).
Significant cost advantage.
Limited computing power, difficult to support AI algorithms and dynamic obstacle avoidance.
Real-time performance is weaker than x86/NV platforms.

Fixed-route AGVs, lightweight material handling scenarios.

‌NV‌

GPU-accelerated AI computing, supports deep learning-based environmental perception (e.g., VSLAM, semantic segmentation).
Strong edge computing capabilities, enabling millisecond-level dynamic path planning.
Supports multi-sensor fusion (LiDAR + vision).
Highest hardware cost (Jetson series unit price exceeds $500).
High development barrier, relies on CUDA ecosystem.

High-flexibility AMRs, complex dynamic environments such as medical/e-commerce.

II. Technical Feature Differences

‌Navigation Algorithm Adaptability‌
- x86: Suitable for running traditional SLAM algorithms (e.g., Gmapping), but offers weaker support for LiDAR + vision fusion solutions.
- NV: Unique advantage lies in GPU-accelerated VSLAM and 3D mapping, with latency < 50ms when processing 1080P video streams.
- RK: Only supports preset path navigation based on QR codes/magnetic strips, unable to achieve dynamic obstacle avoidance.
‌Deployment and Maintenance Costs‌
- x86/NV require additional cooling systems, with overall power consumption 3-5 times higher than RK solutions.
- RK solutions do not require dedicated cooling designs, reducing hardware maintenance costs by over 60%.
‌Development Ecosystem Comparison‌
- NV: Provides JetPack SDK and Isaac Sim simulation toolchain, shortening AI model deployment cycles.
- x86: Relies on the ROS/ROS2 open-source community, offering high flexibility for secondary development.
- RK: Primarily geared towards basic motion control development, lacking AI toolchain support.

III. Selection Recommendations

‌Prioritize NV platform‌: For AMR scenarios that need to handle dynamic obstacles (e.g., human-robot collaborative work) and frequently changing environments.
‌Recommend RK platform‌: For AGV material handling projects with fixed processes and budget sensitivity (e.g., automotive assembly lines).
‌Consider x86 as a compromise‌: For moderately complex AMR clusters that need to balance computing power and cost (e.g., electronics manufacturing workshops).