Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Robbyant Unveils LingBot-Depth 2.0 with Enhanced Spatial Perception for Robotics
Chinese AI company Robbyant has launched LingBot-Depth 2.0, a next-generation spatial perception model designed to enhance robotic navigation in complex environments. This model builds on the previous LingBot-Depth, utilizing the Masked Depth Modeling technique and trained on 150 million samples, achieving top results in 12 out of 16 depth completion benchmarks. Notably, it reduces depth error by over 50%, improving accuracy in challenging indoor settings. The significance of LingBot-Depth 2.0 lies in its ability to accurately perceive transparent and reflective surfaces, areas where traditional depth cameras often struggle. The model's advancements are attributed to LingBot-Vision, a visual foundation model that employs a unique “boundary structure” pre-training objective, enabling sub-pixel-level boundary localization. Despite being trained on a smaller dataset of 160 million images, it demonstrates robust performance across various robotic vision applications, enhancing object boundary detection and tracking. Looking ahead, Robbyant's collaboration with Orbbec aims to integrate LingBot-Depth 2.0 into new hardware solutions for robotics data collection. The RGB-D EGO device, part of Orbbec’s Robot-Free Data Collection Hardware Platform, will feature a customized version of the model. Future updates are expected to further enhance depth completion and spatial structure understanding, providing a solid foundation for training embodied AI systems in real-world scenarios. No further timeline was disclosed at the time of publication.
AI and Robotics
Ant Group Unveils Groundbreaking Spatial Perception Model for Robots
Ant Group's Robbyant has unveiled LingBot-Depth 2.0, an advanced spatial perception model designed to enhance robot vision in complex environments, such as those involving glass and mirrors. This innovative model, which operates with just 1.1 billion parameters, demonstrates superior performance compared to larger models while requiring less training data. The launch, which marks a significant milestone in artificial intelligence technology for robotics, reflects ongoing efforts to improve the capabilities of robots in navigating and interpreting their surroundings effectively.
Robotics AI Computer Vision Depth Perception
Robbyant Unveils LingBot-Depth 2.0 and LingBot-Vision to Redefine Robotic Spatial Perception
Building upon the success of LingBot-Depth, which pioneered the Masked Depth Modeling (MDM) technique to resolve depth sensing challenges for transparent and reflective surfaces, LingBot-Depth 2.0 represents a massive scale-up in training data and performance.
Fortsense Develops Single-Chip RGBD Spatial Cameras for Physical AI Perception
Fortsense Technologies is making significant strides in the field of imaging technology with its development of single-chip RGBD spatial cameras. These innovative cameras combine color and depth perception into a single unit, offering a streamlined alternative to the traditional combination of cameras and LiDAR systems. The company's focus is on enhancing the capabilities of autonomous vehicles and robotics, sectors that increasingly rely on advanced sensing technologies for navigation and environmental understanding. By integrating both color and depth data into one chip, Fortsense aims to improve efficiency and reduce costs in these applications. The initiative is part of a broader trend towards more compact and effective sensor solutions in the rapidly evolving landscape of autonomous technology.
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