The Tool Desk
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Start with the task, not the AI computer
A mobile robot that maps a building, an arm that handles objects, and a humanoid have different mechanical, sensing, power, and control requirements. Before selecting components, define what the robot must do, its operating environment, and constraints such as payload, reach, terrain, speed, precision, and contact with people or objects. Those choices determine what the robot must sense and how it must move.
The following table describes the main parts of the system. It is a selection guide, not a compatible bill of materials; the available sources do not establish specific products or a universally suitable kit.
| Part of the system | What it does | What to decide |
|---|---|---|
| Mechanical platform and end effector | Provides the body, locomotion or joints, and the tool that interacts with the environment. | Robot form, terrain or reach, payload, speed, precision, and intended contact. |
| Actuators and motor-control electronics | Turn commands into movement; drivers and feedback support the control approach required by the design. | Motor or servo type, driver compatibility, required feedback, and motion-control needs. |
| Sensors | Measure the environment and the robot’s own state. | What must be observed, sensor range and field of view, lighting or environmental conditions, update rate, calibration, and interfaces. |
| Power and wiring | Supply and distribute power to compute, sensors, and actuators. | Supply capacity for the actual loads, including peak actuator draw; regulation, distribution, wiring, and safe motion isolation. |
| Compute and controller | Run low-level control and higher-level robotics, perception, planning, or AI software. | Workload and latency, platform compatibility, power and thermal limits, storage, interfaces, and development ecosystem. |
Hardware: what the robot needs
Mechanical platform, actuators, and motor control
Choose a base, wheels or other locomotion, joints, and an end effector that can carry out the task. The required payload, reach, speed, terrain, and forces during contact all constrain the mechanical design. Motors or servos also need suitable drivers; where the design requires closed-loop control, the system needs appropriate feedback as well.
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Do not assume that a motor can be controlled directly by a general-purpose computer. The control electronics and software interface must match the actual actuator and the robot’s motion requirements.
Sensors matched to the job
Select sensors for information the robot needs to act. A mobile robot doing mapping may need range sensing and localization inputs; a manipulator may need vision and joint feedback. Force/torque or other contact sensing may be useful when a task depends on measuring contact, but it is not a universal requirement.
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NVIDIA’s Isaac Sim learning exercises use RGB cameras, 2D lidar, and IMUs as examples of robot sensors. That curriculum is not a prescribed sensor list for every build. Sensor choice also depends on range, field of view, lighting and other environmental constraints, update rate, calibration, and connection to the rest of the system. NVIDIA’s Isaac Sim learning path covers these sensor examples alongside robot construction and control.
Power, electronics, and safe motion
Plan a power source and distribution system for the selected compute, sensors, and actuators, including peak actuator draw. The design may need regulation, motor drivers, wiring, and a way to stop or isolate motion safely. There is no general voltage, current, or battery rating that can be recommended without knowing the selected hardware and application; the cited platform documentation does not set universal power or protective-design values.
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Compute and low-level control
A build may use a microcontroller or real-time controller for deterministic low-level motor and I/O work, alongside a higher-level computer for ROS 2, perception, planning, and AI workloads. A GPU-equipped edge computer can help with demanding inference, but a simpler robot may not need one. Compare candidate compute platforms against the workload and latency, power and thermal limits, storage, sensor interfaces, and software compatibility rather than choosing by AI capability alone.
Software: connect sensing, control, and behavior
Drivers and hardware interfaces
Software needs a supported path to each physical device: drivers and hardware interfaces for actuators and sensors, plus configuration that exposes the relevant commands and state. ROS 2 control examples show joint command and state interfaces, as well as sensors exposing state such as force and torque. ROS software cannot control an arbitrary motor or read an arbitrary sensor without an appropriate hardware interface and compatible configuration. A ROS World 2021 example illustrates these interfaces in a ROS 2-powered robot.
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Perception, estimation, control, and task logic
Above the hardware interfaces, the software stack processes sensor data, estimates the robot’s state, controls motion, and runs task logic and diagnostics. Add navigation when the robot must move through an environment, or manipulation and motion planning when it must move an arm or handle objects. The exact packages and division of work depend on the robot and task.
ROS 2, Isaac ROS, and Isaac Sim are choices—not universal requirements
ROS 2 is a documented foundation for robot applications, not a requirement imposed on every physical AI robot. NVIDIA describes Isaac ROS as an open-source ROS 2 foundation with accelerated robotics libraries and models. Isaac ROS is an optional route for builders who want those packages and a compatible deployment platform. NVIDIA’s Isaac ROS overview describes its role in workflows from simulation toward Jetson deployment.
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NVIDIA Isaac Sim is another optional tool: its learning material covers robot construction and control, ROS 2 integration, URDF asset import and physics, synthetic-data generation, and software-in-the-loop and hardware-in-the-loop workflows. Simulation can help develop and test software before hardware is deployed, but success in simulation alone does not establish that a robot will behave safely or reliably in its physical environment. The Isaac Sim learning path details those topics.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Check platform compatibility before choosing hardware
NVIDIA’s Isaac ROS getting-started documentation currently 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 only ones it tests and officially supports for that Isaac ROS documentation version. These are version-specific Isaac ROS platform-support details—not minimum requirements for ROS 2 or for building every physical AI robot. Check the current Isaac ROS platform matrix before buying a board or updating software, and verify the exact board, JetPack, and Isaac ROS release combination.
A practical build sequence
- Specify the job and environment. Write down what the robot must do, where it will operate, what it must carry or reach, and any relevant terrain, speed, precision, or contact constraints.
- Choose the robot form and motion system. Select the base, locomotion, joints, and end effector that suit the task; then identify compatible actuators, drivers, and required feedback.
- Identify what it must sense. Choose sensors for the information required by the task, and check their operating conditions, calibration needs, update rates, and interfaces.
- Plan power and safety around the chosen hardware. Account for compute, sensors, and actuator loads, including peak draw; design the distribution, wiring, and means to stop or isolate motion for the application.
- Choose compute and a software route. Match controllers and computers to low-level timing, higher-level workloads, interfaces, thermal and power limits, and compatibility. Decide whether ROS 2, Isaac ROS, or simulation tools fit the project; none is mandatory for every robot.
- Integrate and validate in stages. Bring up hardware through its drivers and interfaces, check sensor state and commanded motion, then test the task logic. Simulation can support iteration, but validate behavior on the physical robot in its intended environment as well.
What this guide can—and cannot—specify
This is a system-level guide rather than a build plan. The topic does not specify a robot type, task, payload, environment, skill level, or budget, so it cannot determine exact component models, a complete compatible parts list, or electrical ratings. Those must be selected for the particular design; the cited material does not establish a universally best product or kit.
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