Figure 1. Auto manufacturing has a growing need for mobile robots to efficiently find their way – even in the face of obstacles and environmental uncertainty. Source: SICKFigure 1. Auto manufacturing has a growing need for mobile robots to efficiently find their way – even in the face of obstacles and environmental uncertainty. Source: SICK

Autonomous mobile robots are becoming essential to modern manufacturing, as they are gradually replacing traditional materials handling systems like conveyors, forklifts and of course, humans. This is especially true in the automotive industry, which — due to its own evolving nature — needs added flexibility and transparency to help build the cars of tomorrow.

Besides improving overall efficiency, these robots can eliminate errors and redistribute labor to more meaningful tasks. In automobile manufacturing, mobile robots deliver parts and components to certain areas in the plant or transport chassis, engines and transmissions along assembly lines.

One of the fundamental challenges of mobile robots is localization, which determines where the robot is with respect to its environment. The mobile robot must locate itself amongst a sea of busy machinery, robots and human personnel, and then use that data to chart its course, actions and its uncertainty. This means mobile robots must be provided with cutting edge technologies to enable production optimization — otherwise the robot is no better than the technology it displaces.

To ensure safe operation and accurate localization and navigation, mobile robots must be equipped with several different types of sensors that essentially serve as the eyes and ears of the mobile robots. Designers of these types of robots must be cognizant of several potential challenges with implementing sensors and their inherent limitations to ensure the successful integration of their mobile robots in the plant.

To provide these mobile robots with the information they need, engineers and designers are utilizing some clever, cutting-edge technologies. The end result is a robot that is flexible, smart and optimizes productivity for the automaker.

What is localization?

Localization is a fundamental capability required by any autonomous robot. Knowledge of the robot's precise location provides a basis for navigating around obstacles within a complex and busy production facility.

Previous generations of mobile robots navigated around a facility by following pre-programmed paths around the production floor. One of the most inexpensive and common ways of navigating mobile robots is by using lines, magnetic strips or other proximity sensors on the floor of a facility. These devices report back to a centralized controller to identify the location of the mobile robot on the plant floor.

Mobile robots that use these types of localization schemes that follow a pre-determined route are best suited to working in highly structured environments in the absence of humans. Such systems have therefore fallen out of favor for production lines that require a high degree of flexibility.

The need for flexibility

Modern automobile production lines require adaptable and flexible manufacturing systems. A great example is as automakers transition their manufacturing from internal combustion engines to electric vehicles. The nature of the vehicle requires a comprehensive change in design, and therefore manufacture.

Modern production systems can be rapidly re-configured with minimal downtime to meet ever-changing consumer and production demands. This allows automobile manufacturers to quickly introduce new products, enabling lower operating cost, faster time-to-market, higher product quality and greater customer satisfaction. Flexibility is an important strategy for expanding customization, addressing specific market demands and keeping throughput as high as possible.

Although flexible manufacturing techniques can potentially increase capital equipment costs and reduce manufacturing throughput due to constant product changes, these costs can be mitigated by implementing technologies that have proven adaptable to different types of environments and processes.

Enter intelligent mobile robots. Robotic systems are used extensively because they can be easily re-programmed for new tasks, and in many cases, they can be seamlessly integrated among the human work force.

The flexible manufacturing systems require mobile robots that are amenable to rapid changes in the production and assembly processes. Yet, this requires more advanced software and sensors on dynamic robotic platforms, which allow them to observe changes in their environment, monitor their own location and motion, and freely and safely navigate and operate within the facility.

Furthermore, these mobile robots must be easily adaptable to new production line layouts with minimal re-configuration and re-programming. Hiring developers to code and troubleshoot robotic systems with each manufacturing change is cost prohibitive.

For all these reasons, mobile robots in an automotive production environment must be able to recognize new obstacles, adapt to new tasks and support the entire manufacturing line with little disruption and expense.

Enabling productivity with the SICK LiDAR-LOC system

Increasingly, mobile robot designers and engineers are turning to LiDAR as the enabling technology for localization. And it is a need that SICK is well prepared to meet.

SICK’s LiDAR localization solutions, LiDAR-LOC for short, addresses the growing need for mobile robots in flexible manufacturing. SICK sensors and software enable mobile platforms to move intelligently within warehouse or production line environments by detecting where obstacles and terrain, such as walls, doors, pillars and posts, are located. Once this information is known by the system, the mobile robots can find their own way in an efficient and safe manner to their desired destinations.

LiDAR-LOC utilizes contour localization, which is a novel algorithm for determining the position of a mobile robot. The calculations are based on obtaining spatial data without the use of external or artificial infrastructure, such as codes, floor markings or tags. The on-board sensors detect the contours of the environment, and the algorithm compares the data to a reference map of the production line. In this manner, the environment in which the mobile robot operates is always up to date.

Figure 2. SICK’s LiDAR-LOC is optimizing mobile robot autonomy with spatial mapping software and sensors. Source: SICKFigure 2. SICK’s LiDAR-LOC is optimizing mobile robot autonomy with spatial mapping software and sensors. Source: SICK

Mapping of the environment is accomplished using the SICK mapping software, SMET, which is based on a simultaneous localization and mapping (SLAM) algorithm. This software can create consistent large-scale maps of up to 250,000 m2. During a typical mapping run, the LiDAR sensor scans the environment and detects the contours of the building and any obstacles. This contour data is used to create a model of the environment and a map for the localization system.

The map is a two-dimensional representation of the environment to localize the vehicle. The map generation process is based on a probabilistic localization algorithm that estimates the position of a mobile robot using only the two-dimensional map and the data provided by the lidar sensor. The localization algorithm was improved to obtain more accurate and robust performance even in difficult environments, such as those found in automobile manufacturing.

To further improve the performance and robustness of the localization process, LiDAR-LOC has an optional built-in functionality to extract reflector information in the environment. This combination of natural contours and reflectors provides a more flexible and reliable localization system if needed for difficult environments.

Users of the LiDAR-LOC system can monitor the performance of mobile robots to ensure that they are following the correct and most efficient routes. For example, the software can find out if manual forklifts are being obstructed in certain areas, or if the mobile robot is taking longer to travel a route by crossing areas with high traffic. Although a route may be the shortest distance, it could require additional time. In addition, users can add time stamping, heat mapping and route planning to increase overall operational efficiency.

This can provide valuable information to ensure continuous improvement and process efficiency.

Implementation of LiDAR-LOC

The LiDAR-LOC system is easily implemented and provides a scalable location solution. It is available as a modular software solution that runs on SICK AppSpace-certified controllers as well as various third-party controllers.

The LiDAR-LOC software can be used with any Ethernet-based LiDAR scanner, including non-safety and safety laser scanners like the SICK microScan3 or nanoScan3. The scanners can be mast-mounted or embedded directly into the mobile robot. The LiDAR sensor locates obstacles in the environment (e.g., walls, doors, racks) and provides it to the PC so that it can calculate its exact location and route that the mobile robot should take. This information is also at the fingertips of the manufacturing engineers and operators for review.

The LiDAR-LOC system has high accuracy and repeatability to less than 10 mm. It can operate on vehicles with speeds up to 3 m/sec with rotation rates up to 45°/sec. The vehicle position is provided at a data rate of up to 33 Hz. The system can also be integrated and adopted for vehicle odometry and reflector detection. The ease of implementation and scalability makes LiDAR-LOC an optimal starting point for developing mobile robotic systems.

Enabling mobile robots in auto manufacturing

To meet the growing need for manufacturing adaptability by automakers, manufacturing engineers have increasing reliance on mobile robots for key materials movement throughout the facilities. But the traditional way these robots moved about — preprogrammed maps or floor decals — limits the ability of manufacturers to adapt to new techniques or needs.

LiDAR is the technology of choice for resolving this. It allows the robot to monitor its environment in real time and make decisions based on their observations. This is especially important in environments that may have personnel working alongside the robots, or for manufacturing cells that are sometimes reassigned or reconfigured.

A system like the LiDAR-LOC is easily integrated into a robotic platform via any Ethernet-based LiDAR sensor. This will automatically feed the data into a central location for analysis and decision-making. In addition, it is highly accurate and repeatable, helping the engineers have confidence in the solution they’ve chosen.

SICK overview

The company behind this technology is one of the foremost leaders in industrial range-finding, localization and mapping. SICK is one of the world’s leading manufacturers of sensors, safety systems, machine vision, emissions monitoring systems, flow measurement, encoders, and automatic identification products for industrial applications. With more than 3,500 patents, SICK continues to lead the industry in new product innovations. The diversity of its product line allows SICK to offer solutions at every phase of production in the logistics, automotive, packaging, electronics, food and beverage, material handling and process automation markets. SICK AG was founded in 1946 and has operations or representation in 65 countries worldwide.

More information about SICK, their LiDAR-LOC, and other sensor technology can be found on the SICK website.