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Simplify a robotics design by choosing sensing, processing, communications, motor control, packaging, and safety as one connected system—not as isolated components. Start with the robot’s task and operating environment, turn them into measurable requirements, then select and validate each subsystem against those requirements. This approach applies to collaborative robots, factory automation, and autonomous mobile robots (AMRs); it does not point to one universally suitable component or architecture.
Why robotics design becomes complex
A robot’s processor must handle more than motion commands. Depending on the application, it may also need to analyze sensor data for perception, navigation, inspection, or safety-related functions. Those demands affect compute capacity, motor control, communications, power use, heat, and physical packaging. A decision made for one subsystem can therefore constrain the rest of the design.
Begin by defining what the robot must do, where it will operate, and how it must respond. A cobot working near people, a fixed factory robot inspecting products, and an AMR navigating a facility have different workloads and constraints. “Robotics system” is not a single design profile.
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Turn the application into design requirements
Write requirements that engineers can use to compare architectures and components. The right measures depend on the task; the overview in Electronic Design’s September 2024 article identifies these considerations qualitatively and does not provide benchmark values.
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- Motion: required speed, positional accuracy, torque, and real-time response.
- Sensing: what the robot must detect, the required resolution, and the conditions in which sensors must work.
- Processing: workload and throughput for motion control, navigation, inspection, or local AI.
- Power and thermal limits: efficiency, power density, heat dissipation, and—on a mobile robot—battery life and travel range.
- Mechanical integration: available space, joint packaging, system weight, cable count, and integration complexity.
- Communications: required interfaces, real-time industrial protocols, software ecosystem, and interoperability with the control architecture.
- Safety: applicable requirements, diagnostics, and the safety functions the system needs.
- Cost and development effort: component and system cost, integration work, and the availability of useful software, reference designs, and safety documentation.
These criteria expose trade-offs early. For example, moving electronics into a joint may reduce cabling and weight, but it also makes power density, thermal management, and packaging more demanding. A local vision workload may reduce dependence on cloud processing, but it consumes onboard processing and power resources.
Choose motor-control architecture with the robot’s packaging in mind
In a conventional arrangement, motor-control electronics can be housed in a control cabinet. The Electronic Design article describes a trend toward integrating motor electronics into robot joints, where the shorter, more distributed arrangement can reduce weight, cabling, and system cost. Those are potential system-level benefits, not guaranteed savings for every design.
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Joint integration is most useful to evaluate when space, cable routing, or moving mass is a significant constraint. It also raises the importance of compact electronics, power efficiency, power density, and heat removal. Compare the integrated option with cabinet-based control using the complete motion and thermal requirements rather than treating fewer cables as the only measure of success.
Texas Instruments’ current robotics design resources illustrate components that may be relevant to motor-control designs, including the DRV8353F three-phase smart gate driver, the AMC0106M05 isolated current-sensing modulator, and the AM2612 real-time MCU. These are examples from a manufacturer’s portfolio, not a comparative assessment or a component recommendation. Verify electrical limits, sensing needs, control requirements, and functional-safety suitability for the specific system.
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Match sensing and processing to the task
Do not add sensors simply because a robot could use them. Specify what information the control system needs, where that information comes from, and how quickly it must be processed. A production-line quality-control task may use camera vision; a safety-related application may use multiple cameras. Neither example makes cameras a universal requirement. The sensing design should follow the task and applicable safety requirements.
Processing can be local or distributed, and the workload determines what makes sense. Edge AI means running AI algorithms on local devices rather than in the cloud. That can support vision use cases, but onboard systems must still meet size, power, heat-dissipation, and cost constraints. Evaluate the complete workload and response needs; the source article does not quantify performance or establish that local AI is appropriate for every robot.
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TI’s robotics resource page spans vision processing, radar, position, proximity, and environmental sensing, as well as processing and motor-control resources. Treat such breadth as a menu of possible design approaches, not a checklist of parts every robot needs. For vision prototyping, TI lists a TDA4VM processor starter kit as an evaluation board with demos and tutorials. Its presence as a development resource does not establish that it suits a particular robot or that it is available through any specific retailer.
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Design safety into the system
Safety is a system requirement, not a feature to bolt on after motion control and sensing have been chosen. The Electronic Design article references IEC 61800-5-2 and ISO 10218 and describes Safe Torque Off (STO) in relation to IEC 61800-5-2. It characterizes STO as a function that prevents force-producing power from being supplied to a motor. STO is one safety function; the required functions and applicable standards depend on the system and its use.
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Do not infer compliance from a component’s presence or from a general description of STO. Determine the applicable requirements for the complete robot and drive system, including diagnostics and integration, and consult the relevant standards and qualified safety expertise. The article provides a design overview, not compliance advice or a safety assessment.
Use development resources to reduce integration work
Once requirements are clear, development kits, software, reference designs, and safety documentation can help engineers explore an architecture. TI lists resources including a robotics SDK for Jacinto processors, functional-safety documentation, an edge AI robotics academy, a motor-control SDK, and a white paper on motor-drive safety assessments. Its page also describes a partner ecosystem for hardware, SDKs, and cloud-based AI tools.
Quick Recap
These resources can inform implementation, but they do not prove that a product or subsystem meets the robot’s requirements. The Electronic Design piece is sponsored technical content, and it presents broad qualitative guidance rather than independent product testing, benchmark comparisons, or measured cost savings. Validate component selection and system behavior against the robot’s requirements.
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