Clobotics trains and deploys GPU-accelerated AI models for robot fleet management, autonomous navigation, and real-time perception — enabling thousands of robots to operate as one.
We build and train custom robotics AI models on NVIDIA GPU infrastructure for fleet management and autonomous operations.
Deep RL models for multi-robot coordination, task allocation, and collision avoidance — trained in Isaac Sim, deployed at scale.
Computer vision models for object detection, SLAM, and scene understanding. Optimized with TensorRT for real-time edge inference.
Path planning and motion control models for dynamic environments. Sim-to-real transfer via Isaac Sim training pipelines.
Time-series models for predicting robot component failures and scheduling maintenance before breakdowns occur.
Cloud-based teleoperation with low-latency video streaming and GPU-accelerated decision support for human operators.
Models compressed via quantization and deployed on NVIDIA Jetson Orin modules for on-robot inference without cloud dependency.
Custom models trained on NVIDIA GPU clusters for robotics workloads.
Multi-sensor fusion model combining LiDAR, camera, and IMU data for 360-degree perception. 30 FPS on Jetson Orin with TensorRT INT8.
Multi-agent reinforcement learning model for fleet coordination. Trained in Isaac Sim with 10,000+ parallel environments on H100 clusters.
End-to-end navigation model for autonomous robots in dynamic environments. Sim-to-real transfer with domain randomization.
GPU-accelerated AI for cloud robotics and fleet management.
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