Applications

Robotics

Compute for mobile robots, arms and cobots

Robotics platforms combine perception, planning and control on constrained hardware, often with real-time requirements and safety certification obligations.

Solutions in this category

Representative platforms with the details engineering and procurement teams shortlist on.

Autonomous mobile robot in a warehouse aisle with sensors visible on its chassis
NVIDIA

NVIDIA Jetson Thor T5000 module

Blackwell-generation robotics module rated at up to 2,070 FP4 TFLOPS with 128 GB of memory.

AI performance
Up to 2,070 TFLOPS (FP4)
GPU
NVIDIA Blackwell GPU with transformer engine and MIG support
CPU
14-core Arm Neoverse V3AE
Deployment
Robot compute bay or autonomous machine, on a carrier board
Humanoid and mobile robots
Multi-sensor autonomy
On-robot vision-language models

Specifications are summarised from publicly published manufacturer material and are provided for orientation only. Always confirm current figures directly with the manufacturer before purchasing or designing in.

Companies working in this category

NVIDIA

Chip manufacturer

Develops the Jetson family of edge system-on-modules, the DGX Spark desktop AI system and the JetPack, TensorRT and DeepStream software stacks used for edge inference, robotics and vision AI.

Santa Clara, California, United States

ADLINK Technology

Hardware manufacturer

Builds embedded computing modules and the DLAP family of deep learning acceleration platforms, including fanless Jetson-based inference systems with Power over Ethernet camera inputs.

Taoyuan, Taiwan

Aetina

Hardware manufacturer

Designs fanless edge AI systems and carrier boards around NVIDIA Jetson modules, including wide-input, wide-temperature platforms for machine vision and mobile robotics integrators.

New Taipei City, Taiwan

Boston Dynamics

Robotics company

Robotics manufacturer building mobile and industrial robots that rely on on-board perception and autonomy rather than remote compute.

Waltham, Massachusetts, United States

Robotics: common questions

Why do robots need on-device AI?
Control and obstacle avoidance loops cannot tolerate network round trips, so perception and decision making generally run on the robot itself.