The Tool Desk
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What hardware does a physical AI robot need?
Think of the robot as a system whose parts must work together. The task determines how it moves and interacts; those choices constrain the motors, sensors, power system, and compute. Before selecting hardware, write down what the robot must do, what it will carry or touch, and where it will operate.
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Mechanical platform and actuators
Choose the body and means of movement around the task: for example, a wheeled base for mobile work, articulated joints for manipulation, or another platform suited to the environment. The robot’s payload, reach, speed, terrain, precision, and expected contact forces all affect the mechanical design.
Motors or servos need suitable drivers and a control path. Where the design requires it, feedback such as joint position or velocity lets the controller know whether the mechanism followed its command. The actuator, driver, feedback device, and software interface must be compatible; choosing any one in isolation can leave you with hardware the rest of the system cannot control.
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Sensors
Select sensors for what the robot must observe, not because a particular sensor list is common in tutorials. A mobile robot mapping its surroundings may need range sensing and localization inputs. A manipulator may need cameras to locate objects and joint feedback to track its arm. Force or torque sensing can be appropriate when the task depends on measuring contact.
NVIDIA’s Isaac Sim learning curriculum uses RGB cameras, 2D lidar, and IMUs as examples in its exercises; these are examples, not a required set for every robot. For each candidate sensor, check useful range and field of view, lighting or environmental limits, update rate, calibration needs, and interface compatibility. NVIDIA’s Isaac Sim learning path covers sensor use alongside robot construction and ROS 2 integration.
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Power, electronics, and stopping motion
The power system must supply the computer, sensors, and actuators, including the actuators’ peak draw. A practical design also needs appropriate voltage regulation and distribution, motor drivers, wiring, and a safe means to stop or isolate motion. The required ratings and protective design depend on the chosen components and application; there is no universal battery size or wiring specification for all physical AI robots.
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Many designs divide work between a low-level controller and a higher-level computer. A microcontroller or real-time controller can handle deterministic motor and input/output tasks where needed. A more capable computer can run ROS 2, perception, planning, and AI workloads. A GPU-equipped edge computer may help with demanding inference, but it is not automatically necessary for a simpler robot.
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Compare compute options by checking supported software, workload and latency, power and thermal limits, storage, sensor connections, and development ecosystem. The right choice depends on the robot’s task and implementation—not on the label “AI.”
What software connects the robot’s parts?
The software stack needs a path from physical devices to useful behavior. At a minimum, account for device drivers and hardware interfaces, sensor processing and state estimation, control, task logic, and diagnostics. A mobile robot may also need navigation; an arm may need manipulation and motion planning. Which functions you need depends on what the machine is meant to do.
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ROS 2 and hardware interfaces
ROS 2 is one documented foundation for building robot applications, but installing it does not make arbitrary hardware controllable. The motors, sensors, and controllers need suitable drivers and configured interfaces that expose the commands and state the software expects. For example, ROS 2 control configurations can expose joint command and state interfaces, while sensors can provide state such as force and torque. The ROS World 2021 hardware-interface example illustrates this connection between hardware and ROS 2 control.
Optional NVIDIA tools
NVIDIA Isaac ROS is an open-source set of accelerated robotics packages and models built on ROS 2. It is an optional choice, not a requirement for every robot. NVIDIA’s current Isaac ROS getting-started documentation lists Jetson Thor and Jetson Orin with JetPack 7.2 and at least 128 GB NVMe SSD in its Jetson platform matrix. NVIDIA says the combinations in that matrix are the ones it tests and officially supports for that documentation version. Treat the listed hardware and software pairing as version-specific support information, not as a minimum specification for ROS 2 or for physical AI robots generally. Check the matrix again before choosing a board or updating software.
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- Arduino Programming, Open Source: miniArm is built on the Atmega328 platform and is compatible with Arduino programming. The programs for miniArm are open-source, and learning tutorials and secondary development examples are available, making it easier for you to develop your robotic hand.
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Isaac Sim is another optional route for constructing and simulating robots, integrating with ROS 2, generating synthetic data, and working through software-in-the-loop and hardware-in-the-loop workflows. The NVIDIA Isaac ROS overview describes a workflow from simulation toward Jetson deployment. Simulation can help you iterate and test software, but it does not by itself establish that a physical robot will operate safely or reliably in its real environment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should you choose parts for your robot?
Work from the job outward. This order helps prevent a common mismatch: buying compute or sensors first, then discovering they do not suit the robot’s mechanics, operating conditions, or interfaces.
- Define the task and environment. Specify what the robot must do, where it will operate, what it must carry or manipulate, and what kinds of movement or contact it will encounter.
- Choose the robot form and mechanical requirements. Set the needed locomotion or joints, payload, reach, terrain capability, speed, and precision. These requirements narrow the actuator and platform choices.
- Choose sensors for the observations the task needs. Check range, field of view, environmental limits, update rate, calibration, and interfaces. Add contact sensing only if the task warrants it.
- Design the control and power path. Match actuators with drivers and the appropriate low-level control hardware. Account for the computer, sensors, and peak actuator demand when planning supply and distribution, and include a safe way to stop or isolate motion.
- Select the higher-level computer and software. Estimate the perception, planning, and AI workload, then verify compute compatibility, latency, thermal and power limits, storage, and sensor connections. Choose ROS 2 and any optional packages only after checking that the hardware has drivers and interfaces for them.
- Develop and validate incrementally. Use simulation where it helps develop or test software, then validate the integrated physical robot in its intended environment. Simulation is not a substitute for checking real hardware behavior and safety.
What depends on the robot type?
| Robot type or task | Design emphasis | Questions to resolve |
|---|---|---|
| Mobile robot doing mapping | Locomotion, range sensing, and localization inputs | What terrain and speed must it handle? What range, field of view, and sensor interfaces suit the environment? |
| Manipulator | Arm mechanics, payload and reach, vision where needed, joint feedback, and motion control | What objects must it handle, how precisely, and does the task require contact sensing? |
| Humanoid or other complex platform | Many interacting mechanisms, sensing, power, control, and safety requirements | What specific task justifies the added mechanical and integration complexity? |
These are design considerations, not complete bills of materials. The exact parts, ratings, and compatible models depend on the robot’s requirements; the available documentation does not establish one universally best product or kit.
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Quick Recap
What to verify before buying or deploying
- Compatibility: Confirm that each sensor, motor driver, controller, and computer has a usable hardware and software interface for the rest of the system.
- Workload fit: Check that compute can meet the intended perception or planning workload within the design’s power and thermal limits.
- Physical fit: Confirm payload, reach or terrain, speed, precision, and feedback are suitable for the task.
- Power and motion safety: Account for peak actuator demand and provide a suitable way to stop or isolate motion.
- Version support: If using Isaac ROS, verify the exact board, JetPack, and Isaac ROS documentation version combination rather than assuming every model in a product family is supported.
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