RoboSense, an AI-driven robotics technology company, has launched AC1, its AI-powered robotic vision platform.
Representing the first product in its Active Camera series, along with the AI-Ready ecosystem, it provides an all-in-one solution for robotic perception development. As the inaugural product in the Active Camera series, AC1 focuses on the fusion of three core sensors: LiDAR, camera, and IMU (Inertial Measurement Unit). This hardware-level data integration in turn enables the combination of depth information, visual semantics, and motion pose.
Leveraging an ultra-wide fusion perception FOV of 120° x 60°; an extended detection range of up to 70 meters (with precise detection of low-reflectivity objects with 10% reflectance at 20 meters); and a Stable ranging accuracy of 3cm@1sigma, the device helps developers meet robotic needs for obstacle avoidance, mapping, and localization, allowing them to focus on core functionality development without the challenges of multi-sensor stacking, calibration, and data conflicts.
The AI-Ready ecosystem will more broadly aim to support developers with basic software tools and open-source algorithms, including the AC Studio all-in-one toolkit, which eliminates the need for redundant development efforts. The open-source SDK includes a suite of tools covering drivers, data acquisition, and fusion algorithms, while the accompanying algorithm library supports advanced technologies such as SLAM, semantic segmentation, and 3D Gaussian splatting, all optimized for mainstream AI computing platforms.
Working within this technology ecosystem, AC1 is designed for diverse applications that require the fusion of depth, color, and motion posture information. Here, RoboSense highlighted that its use cases could include humanoid robots, drones, digital twin environments, 3D scanning, environmental monitoring, and bulk material tracking. The company further underscored the potential of AC1 in supporting further applications such as autonomous driving, industrial robotics, and home robotics.
