Simplify a robotics design by treating motion control, sensing, compute, communications, power, packaging, and safety as one connected system—not as independent component choices. Start with the robot’s task and operating constraints, then choose only the capabilities needed to meet them. That approach helps avoid unnecessary hardware and integration work while keeping performance and safety requirements visible.
Start with the robot’s job and workload
Define what the robot must do before choosing processors, sensors, or motor electronics. A collaborative robot, a factory robot, and an autonomous mobile robot can share design concerns, but their workloads differ. A system built for precise motion control may have different sensing and compute needs from one that must navigate a facility or inspect products on a production line.
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Write down the task and the conditions that determine success. Include required speed, positional accuracy, torque, sensing resolution, processing throughput, and real-time response. These are design dimensions, not values that can be chosen from a general-purpose robotics guide: the required levels depend on the application.
- Motion: What movements and orientations must the robot achieve, and what accuracy and response does the task require?
- Perception and navigation: What must the robot detect, inspect, or use to determine where it is?
- Operating environment: Is it stationary, mobile, or operating near people? What constraints does that place on power, packaging, and safety?
- Integration: Which interfaces, real-time industrial protocols, and software must work with the control architecture?
More capable robots may need to process more data for perception, navigation, and motion control. Because these workloads interact, changing a sensor can affect compute needs; moving electronics into a joint can affect thermal and power constraints. Keep those dependencies visible while defining requirements.
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Choose motor control and packaging together
Motor-control electronics are increasingly being integrated into robot joints rather than kept entirely in control cabinets. Joint-level integration can reduce cable count, weight, and system cost, but it also concentrates electronics in a tighter space. That makes power density, efficiency, and heat dissipation important design considerations.
Compare the two approaches against the actual system, rather than treating integration as an automatic improvement:
| Design consideration | Electronics in a control cabinet | Electronics integrated into a joint |
|---|---|---|
| Packaging | Electronics are located outside the joint. | Electronics must fit within the joint’s available space. |
| Cabling and weight | May require more cabling between the cabinet and motors. | Can reduce cabling and system weight. |
| Thermal and power density | Consider the cabinet’s power and thermal limits. | Higher integration increases pressure on power density, efficiency, and heat dissipation. |
| Cost and integration effort | Assess system-level cost and integration requirements for the architecture. | Potential system-cost reductions must be weighed against packaging and integration demands. |
The comparison is qualitative: the available design overview does not provide measured savings, thermal limits, or a benchmark showing that one arrangement is better in all applications. Evaluate the complete drive and mechanical system, including the available space and cooling path.
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Match sensing and processing to the task
Choose sensors for what the robot must perceive, and choose processing capacity for the data and response those sensors require. Camera vision can support production-line quality control; multiple cameras can support safety-related applications in a car or mobile robot. These are examples, not a requirement to use cameras in every robot.
Robotics sensing can also involve radar, position, proximity, or environmental measurements. Each option serves a different need, so specify the measured quantity and required performance before selecting hardware. Avoid adding sensing simply because it is available: additional sensors can bring additional data, processing, interfaces, and integration work.
Consider edge AI where local vision processing helps
Edge AI means processing AI algorithms on a local device rather than sending the workload to the cloud. Local processing can support vision use cases, but it brings constraints that matter in a robot: board or package size, power consumption, heat dissipation, and cost. Check that the processing platform can handle the intended workload within those limits.
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For engineers exploring vision-based robotics, Texas Instruments lists a TDA4VM processor starter kit as an evaluation board with demos and tutorials for prototyping vision applications. It is a development resource, not evidence that the kit is suitable for every robot. Confirm the processor, interfaces, software, and power and thermal characteristics against the intended system before committing to an architecture.
Make safety part of the system architecture
Safety requirements affect drives, controls, sensing, diagnostics, and system behavior. Identify the applicable requirements and standards for the robot and its environment early, rather than treating safety as a feature to add after the motion system is selected. The design overview references ISO 10218 and IEC 61800-5-2 but does not provide compliance advice; determining what applies requires consulting the relevant standards and carrying out the appropriate safety assessment.
Understand what Safe Torque Off does
The Electronic Design article describes Safe Torque Off (STO), by reference to IEC 61800-5-2, as a function that prevents force-producing power from being provided to a motor. STO is a drive safety function associated with stopping a motor safely and preventing unexpected startup. It is not a substitute for evaluating the complete robot’s safety requirements, and the article’s description should not be treated as a direct quotation from the standard.
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When considering a drive or safety module, establish which safety functions the system needs, how they will be implemented, and what documentation and diagnostics are required. Do not infer system compliance from a component’s description or a design-resource page.
Plan communications and integration before selecting components
Confirm the control architecture’s required interfaces and real-time communications early. Texas Instruments’ robotics resources list industrial protocols including EtherCAT and PROFINET, alongside motor-control, sensing, embedded-processing, and functional-safety resources. A protocol appearing in a manufacturer’s portfolio does not establish that a particular device, board, or complete robot supports the configuration you need.
- Identify the interfaces and protocols required by the robot’s controller and connected equipment.
- Check compatibility across the selected processors, drives, sensors, and software.
- Account for timing and real-time response requirements in the intended workload.
- Include development tools, reference designs, and safety documentation in the integration assessment.
Use a subsystem checklist to narrow the design
Before choosing parts, compare candidate architectures against the same set of requirements. This keeps trade-offs explicit and makes it easier to spot a subsystem choice that shifts complexity elsewhere.
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- Define the application: Specify whether the design is for a cobot, factory automation, an AMR, or another robot, and list its motion, navigation, inspection, and safety-related workloads.
- Set performance requirements: Record the needed speed, positional accuracy, torque, sensing resolution, processing throughput, and real-time response. Do not substitute unverified generic figures for application requirements.
- Set power and thermal limits: For mobile systems, consider battery life and travel range. For integrated electronics, assess efficiency, power density, and heat dissipation.
- Set packaging constraints: Account for joint space, board or package size, cable count, system weight, and integration complexity.
- Determine safety needs: Identify applicable robot and drive requirements, diagnostics, and whether STO or other safety functions are needed.
- Confirm communications and software fit: Check required real-time protocols, interfaces, interoperability, and the selected control software ecosystem.
- Assess cost and development effort: Consider component and system cost, integration work, and availability of development software, reference designs, and safety documentation.
- Validate the complete system: Check component selections against the robot’s electrical, mechanical, thermal, performance, and safety requirements before treating a reference design or evaluation board as a solution.
Use design resources as implementation aids
Texas Instruments’ robotics design resources cover motor control, embedded processing, sensing, industrial communications, functional safety, and edge AI. The listed resources include a robotics SDK for Jacinto processors, a motor-control SDK, functional-safety documentation, an edge AI robotics academy, and a white paper on motor-drive safety assessments. These materials can help engineers investigate implementation options; they do not replace system validation or establish that a particular component is the right fit.
The resource page also lists examples such as the DRV8353F three-phase smart gate driver, the AMC0106M05 isolated current-sensing modulator, and the AM2612 real-time MCU. Their inclusion is not a comparative recommendation. Choose components only after checking the system’s electrical and functional requirements. The design overview offers qualitative guidance rather than independent benchmarks or product comparisons.
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