Optimizing Control and Design for Industrial Robotics

Optimizing control and design for industrial robotics

Lalindra Jayatilleke Product marketing engineer, Processors Kazunobu Shin Systems engineer, Processors Jason Reeder Systems engineer, Processors Sunil Oak Applications engineer, Processors

Texas Instruments Introduction

With the rise of factory automation, robotics has become increasingly important in the production of goods. Robotics can increase manufacturing efficiency, reduce cost and increase quality. Globally, manufacturers are relying increasingly on robotics to churn out products with increased speed and consistency.

This white paper serves as an introduction to industrial robots in general and more specifically about robot control units. It covers some important applications and system technologies that would help understand how industrial robots control units are architected, as illustrated in Figure 1.

Backplane power Backplane data

Backplane Backplane Backplane Backplane Backplane Backplane Output Backplane Backplane Input Prot. Input Prot. Input Prot. Input Prot. Input Prot. Prot. Comms Comms Comms Comms Comms Comms Comms Comms

Point of Digital Point of Digital Digital Point of Digital Input Prot. Point of Digital Point of Digital Point of Digital Load Process. Process. Load Process. Load Process. Load Process. Load Process. Load Process. Point of Temp. Isol. Isol. Isol. Isol. d I + V I + V RTC Load Data Isol. Data Isol. Data Isol. Data Isol. PFC High-side Supply power power power power Controller Sensing switches Sensing Digital Industrial Front-End Front-End Front-End ol Module Security Process. PoIE Front-End Front-End Front-End

Ethernet Power Power Power Guar

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Output Output Cameras Prot. Prot. Protection Protection Protection Protection Power Stage

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ea Scanner Safety PSU Distributor CPU module iPC Comms IO IO IO

Robot Controller Drive: 1× / Axis

AC mains

5th axis 6th axis 7th axis

4th axis Backplane Input Prot. Comms

Point of Digital 3rd axis Load Process.

Isol. Data Isol. Power

Front-End Front-End End-effector Power connector Protection 2nd axis Welding Deburring Paint Spray Tooling: non-prehensible 1st axis Teach Pendant Grippers: prehensible; grasp and move objects Power Camera

Keys Panel Po

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IOs Control Robot Arm

Robot Controller

Mechanical Electro- Fingers Vacuum Collet mechanical Safety Guards

Figure 1: Typical system components in an industrial robot system.

For more information on this topic, read our how sensor data is powering artificial intelligence (AI) in robotics white paper.

Optimizing control and design for industrial robotics 2 June 2019 Applications run their business without robotics or some form of automation. Some example applications for robotics Applications that benefit from industrial robots are are shown in Figure 3 on the following page. product assembly, material handling, machine tool management, packaging, welding and logistics. The advantages robotics provide are achieved by advances in functional safety and reliability Logistics robots especially have become of systems designed by robot vendors. Texas increasingly important in online retail. These are Instruments (TI) has a wide range of processors that autonomous robots that assist in gathering items for fit perfectly for these applications, includingSitara™ shipment from warehouse inventory, and efficiently processors for the robot central processing unit enable shipment. Figure 2 shows an example (CPU) and Hercules™ Arm® Cortex®-R4 and reference diagram for an autonomous guided -R5 based microcontrollers for functional safety vehicle (AGV). Online retailers are starting to utilize applications. Customers looking to achieve safety autonomous logistics robots for order fulfillment. integrity levels (SIL) in their robot products can do For large retailers, it would be nearly impossible to

Load weight Autonomous guided vehicle (AGV) / measurement: Autonomous mobile robot (AMR) or other logistics robots tracks load presence ADC and compatibility with system specs AMP

MUX E-Fuse & Battery Input Gas gauge sensing power protection charger Weight or module: lidar force sensing Battery management system front-end

Input power protection DC/DC LDO PMIC

Point of load regulators IMU sensing module: radar

Ethernet/ Temperature/ ARM/ASIC/ Level RS-485/ Supervisor Logic TVS/ESD x86/FPGA shifter LVDS

sensing Ethernet/ module: House keeping Motion controller RS-485/ TVS/ESD ultrasonic LVDS SPE / 10/ Analog motor Digital motor CAN/ 100/1000M- driver or driver RS-485/ ... BASET Signal input- Camera Sensor hub output protection or Industrial Low voltage motor control Fieldbus Ethernet

Drive might be integrated or on same PCB as motion controller

Integrated drive

motors for driving wheels & one for load lifting

Figure 2: High level block diagram for an autonomous guided vehicle or robot.

Optimizing control and design for industrial robotics 3 June 2019 so by designing their systems leveraging Hercules critical for high-performance robot operation and devices, followed by system certification from an therefore requires high data throughput and low independent assessor. latency. The typical robot controller system uses

Another growing application for robotics is an application-specific integrated circuit (ASIC), unmanned aerial vehicles (UAV) also known as PCIe or Ethernet base for the backplane system drones. With advancements in sensor and battery bus. In addition to these common modules of the technologies, drones have become common place robot controller system, an additional functional in agriculture applications such as crop monitoring module can be added to extend the capability of and soil and field analysis. Drones are also used in the robot arm based on the requirements from some countries for vaccine and donor blood delivery various applications.

services to rural regions. As technology evolves, Robot Controller System more applications in robotics will emerge. Main Servo Functional I/O CPU Processing Safety Module Module Module Module

System Backplane

Figure 3: Examples of robot applications. Industrial Sensor Vision Sequence Comm Module Module Module Module Industrial robot controller systems High-end industrial robot controller Figure 4: Robot controller system example for high-end industrial High-performance industrial robot systems in robots. factories utilize robot arms, controllers and teach pendants. Various types of robot arms are available Sitara processors can cover the functionality and depending on the application. Each robot arm performance needs required by most functional has their own number of controlled axes and modules in the high-end robot controller system payload capacity. The controller within the system category. Sitara AM57x processors can provide is designed to manage many types of robot arms high processing performance required by the through a configurable and flexible system based main CPU module and servo processing module. on modular system architecture. See Figure 4 Digital signal processors (DSPs) provide for a typical system block diagram for a high-end additional signal processing performance required industrial robot. As far as scalability, the controller for servo and motion signal processing in lower system supports functional modules and the power consumption. Sitara AMIC processors capability to scale the performance and functionality are optimized for industrial communication and based on the system configuration. The basic can be used as the interface to the system robot controller system includes individual modules backplane bus when an industrial communication supporting the main CPU, motion control, input / protocol is needed. Sitara processors can support output (I/O) control, sensor(s), functional safety and multiple industrial communication protocols industrial communication. The backplane system with programmable real-time unit industrial bus to connect multiple functional modules is communications subsystem (PRU-ICSS). They can

Optimizing control and design for industrial robotics 4 June 2019 also reduce development cost and time required for Controller for Cartesian robots developing separate modules for supporting various The robot controller solution for Cartesian, or industrial communication protocols. single-axis, robot is much simpler and only requires Integrated robot controller for cobot and basic functionality for controlling one or two axes SCARA robot motors. However, current controller systems are

The control system for a collaborative, or selective based on a few MCU and ASIC devices given that compliance assembly robot arm (SCARA), robot robot control and motor control are separated and is simpler than a high-end robot controller, as it additional industrial communication IC is required. typically controls less axes and has a slower speed Sitara AM437x and AMIC120 devices feature than high-end robots. Figure 5 shows an example multi-protocol industrial communication, robot/ system block diagram for a single-board robot motion control and motor control including encoder controller system for collaborative or SCARA robots. interface with a single device and can support The control system can also be much simpler and Cartesian robot controllers with one or two axes as can consist of a single board or a few boards. At shown in Figure 6. the same time, smaller size and lower system cost AM437x/AMIC120 Processor becomes more important to save factory space Power Industrial Ethernet Control and integrate the controller as a part of an industrial MPU M robot arm system. Because a SCARA robot can be Feedback placed much closer to humans, functional safety becomes more important to use a robot without I/O other safety system such as safety fences. Figure 6: Single-chip robot controller system based on AM437x or AMIC120 processors. Single-Board Robot Controller System

Industrial communication Functional Motor Main CPU There are over a dozen different communication Safety Control protocols on the market for industrial Ethernet, fieldbus and position encoders, each with its own pros Industrial and cons. EtherCAT®, PROFINET® and EtherNet/ Comm Sensor I/O Interface Industrial Protocol are some of the most popular Ethernet-based protocols in the servo drives market. Hiperface® Digital Servo Link, EnDat 2.2

Figure 5: Single-board robot controller system for collaborative or and Bidirectional Interface for Serial/Synchronous SCARA robots. C are among the more popular position-encoder protocols for other types of industrial robots. Sitara AM57x and AM65x processors can support most of the required features and functionalities with Many of these protocols have ASICs that allow integrated industrial communication, motor control users to attach to host processors to support and functional safety and realize robot controller specific communication protocols. In some cases, system with fewer system components. with a multi-chip solution, the protocol’s stack runs on the host processor and the ASIC performs the

Optimizing control and design for industrial robotics 5 June 2019 media access control layer. Manufacturers who Highly integrated MCUs and processors can also only plan to support a single protocol prefer this help streamline functional safety development. distributed architecture, since ASICs are typically Developed according to the IEC-61508 safety optimized for specific communication standards. standards, TI Hercules MCUs include features Once the need to support multiple protocols enabling functional safety in hardware and detect arises, a multi-chip solution loses its attractiveness potential failure modes with quick response time. because of the new development effort and costs Hercules MCUs are also used in applications and the maintenance of multiple versions of their requiring a dedicated processor to perform a boards for each protocol. specialized function. In these systems, the Hercules

By leveraging integrated multiprotocol support onto MCUs function as the “safety checker” that ensures the host processor, designers can save costs, board that the system is always maintained in a safe state space and development effort, while also minimizing of operation. Sitara AM65x Arm-based processors the latency associated with communication between feature two or four Arm Cortex-A53 cores and external components and the host. A single platform include a dual-Arm Cortex-R5F MCU subsystem to supporting multiple standards enables you to make it easier for customers to develop functional maintain a single board for the different versions of safety applications. To learn more about functional your end product. Another consideration is the need safety, read our white paper titled, “The state of to support Time Sensitive Networking (TSN) and functional safety in Industry 4.0.” then desigining a solution that’s flexible enough to Enabling machine learning adapt to evolving TSN standards. The Sitara AM6x processor family provides a solution through its As robotic technologies advance, so do flexible PRU-ICSS, which enables gigabit TSN as complementary sensor technologies. Much like well as traditional 100-Mb protocols like EtherCAT. the five senses of a human being, combining different sensing technologies offers the best Functional safety considerations results when deploying robotic systems into Industrial robots have been used for over five changing and uncontrolled environments. Even the decades in widely varying applications, ranging simplest tasks that a robot performs will depend on from spot welding in manufacturing to the pick- machine vision to feed data into machine learning and-place operations in the packaging industry. The technology. Grasping an object, for example, emergence of more complex robotic applications without pre-determined locations and motions and systems in recent years has led to advances in would be impossible without leveraging machine functional safety capability of MCUs. This enables vision to reconstruct a 3D image and utilizing use of robots in new application environments machine learning algorithms to translate this visual and enables robotic automation that can operate information into a successful action on the part of in closer quarters with humans in the production the robot. environment. While the use of collaborative robots Machine learning, and its branch named deep in industrial production is only now beginning, there learning, has recently become a popular approach has been a lot of work already in the development to processing all the data collected from sensors of the required safety capabilities residing in sensors to enable the system to make intelligent decisions. and processors and in the standardization of Sitara AM5749 processors enable designers to run industrial robot requirements. machine learning inference at the edge. Machine

Optimizing control and design for industrial robotics 6 June 2019 learning technology helps simplify programming and safety levels, sensors and software are all important enables new ways to operate robots. when considering the application the robot is

Software is also increasingly important in the trying to address. When developing any robotics development and deployment of robots and application, it’s important to have options when designers need an easy-to-use, flexible software evaluating system components. Scalable hardware platform to add features to their products as and software solutions like Sitara processors or needed. Solutions like the Processor SDK Hercules MCUs give designers the flexibility to (software development kit) allows designers to create a variety of capable solutions for robotics. maximize their software reuse and migrate software Additional resources: across the TI processor portfolio. The Processor • Learn more about TSN in our white paper SDK is a unified software platform for TI processors titled, “Time-sensitive networking for that enables quick setup and out-of-the-box industrial automation.” access to benchmarks and demos. Additionally, specialized versions of the Processor SDK Linux • For more information about how sensors are include support for the ROS (Robot Operating being used in robotics, download our white System) framework utilized by developers of paper titled, “How sensor data is powering AI robot controllers. in robotics.” • Read our white paper titled, “Bringing machine Conclusion learning to embedded systems” to learn more There are a variety of system considerations a about machine learning with Sitara processors. robotics designer has to make when designing a • Download our reference design for Processor robot. Determining the central processor, system SDK Linux in robotics applications.

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