The landscape of robotics business applications is evolving. Robots are being called upon to handle a broader variety of tasks. They are expanding beyond roles as stationary workhorses in areas such as manufacturing to become mobile machines that address a wider array of challenging automation duties. Robots increasingly operate autonomously and their abilities to traverse changing and unstructured environments are improving.
“Lidar technology is an essential ingredient in robotic autonomy and navigation. It allows mobile robots to extend outside controlled situations with pre-defined tasks and function in unfamiliar and unpredictable settings,” said Frank Bertini, UAV and Robotics Business Manager at Velodyne Lidar. “Lidar sensors provide a constant stream of high-resolution, 3D information about the robot’s surroundings, including locating the position of objects and people.”
Lidar enables the robot to not only identify the presence of an entity but also determine in real time if it is a human or object. This allows the robot to assess appropriate risk behavior models, which is essential for managing safety in robot-human collaboration. Also, lidar, which does not recognize the identity of a person, avoids the privacy problems created by robots that use cameras as a sensing technology – an important factor in retail and other applications.
Mobile robots operating outside can rely on geolocation capabilities, such as GPS along with sensing technologies including lidar, to determine where they are located and where they are headed. That is not typically possible indoors. Mobile robots operating indoors employ simultaneous localization and mapping (SLAM) technology that utilizes lidar’s data to build a map of the robot’s environment and locate the robot within that map. The benefits provided by SLAM technology include “easy navigation without reliance on external technologies and real-time formation of 3D maps with reduced cost and power requirements,” according to Global Market Insights.
Among the applications for mobile robots are:
* Distribution Centers, providing more efficient pick and palletization processes in warehouses.
* Food and Grocery Delivery, navigating sidewalks, pedestrians, and more while bringing hot or cold food to a customer.
* Retail, scanning aisles for product replenishment needs and answering questions for shoppers.
* Security, roaming corridors to identify security issues, such as unauthorized people, and open doors and windows.
* Industrial Automation, providing safety and efficiency in agriculture, construction, logging, maritime, mining, pipeline inspection, and railway.
Market research analyst firm Technavio forecasts that the global market for autonomous mobile robots will grow at a CAGR of more than 14 percent from 2017 to 2021, reaching more than $8 billion in value in 2021. Lidar is crucial in the expanded development and deployment of mobile robots to enhance productivity and efficiency in business operations.
Let’s take a closer look at the central lidar capabilities needed for mobile robotics success.
Field of View. Field of view measures the angular view captured by lidar sensors, a capability particularly important in navigating complex situations like a person stumbling near the robot, causing the machine to reroute or stop completely. It encompasses horizontal – the angle of the view to the peripheral edges– and vertical – the view from the ground up to the sky or a ceiling. A lidar sensor with a full 360° view, such as Velodyne sensors, means the entire environment around the robot can be seen while operating. The sensor’s vertical view provides visibility into what’s ahead, such as a tall object or overhang. Since each laser within the sensor is pointed at a different vertical angle, even negative obstacles such as a curb or hole can be detected.
Range. The range required for a lidar sensor is application specific – with needs spanning short ranges to work in indoor environments, such as a retail store, to long ranges for robots that operate outdoors. Also, how far a laser sensor can see impacts how fast a robot is able to move, and how well it is able to plan. Faster robots and vehicles traveling over 30 mph may need to see 200 meters or more.
Power Consumption. Managing energy requirements is a significant challenge in mobile robot development. The lower the power consumption, the more time a robot can operate between charges. Lidar sensors with modest power demands – 8 watts, for example – help extend a robot’s battery life. Capturing higher amounts of 3D data points can also decrease the raw compute load for deep learning/machine learning algorithms which use GPU’s. One of Velodyne’s customers was able to achieve a 30 percent drop in GPU power consumption by installing an additional sensor to double their lidar points per second. A key value indicator for 3D lidar is the number of points per second that it detects per watt that it consumes.
Multi-Environments. Outdoor robots need the ability to operate in both dry and wet weather conditions as well as on hot summer days and freezing winter nights. Lidar systems need to sustain high-stress environmental condition testing for temperature cycling, water ingress, and much more to demonstrate their ability to operate in a range of environments, including not-so-human-friendly conditions. Lidar sensors which are rated at IP67 (for more information on IP code, read here) are able to handle this wide variety of operating conditions.
Outdoor applications should also consider the wavelength of the laser to be used. If the robot will operate in precipitation, such as rain or snow, 905nm laser has been proven to work more reliably than 1550nm and other longer wavelengths (for more on laser wavelengths and water absorption, read here).
ROS Integration. According to the Open Source Robotics Foundation, the “Robot Operating System (ROS) is a flexible framework for writing robot software. It is a collection of tools, libraries, and conventions that aim to simplify the task of creating complex and robust robot behavior across a wide variety of robotic platforms.” To enable companies to take advantage of ROS-ready mobile robotics platforms, lidar providers need to develop and maintain ROS drivers for their sensors. For instance, Velodyne sensors have built-in ROS integration.
Form Factor. Lidar sensors need to be available in form factors that support a wide variety of robot applications, such as heavy-duty industrial robots for manufacturing; autonomous mobile robots in warehouses; inspection robots that navigate the narrow confines of sewer pipes; and multi-legged robots the size of dogs. In these diverse applications, lidar sensors must also be able to operate when oriented in any direction, including sideways and upside-down.
Reliability. Lidar systems for robotics need to demonstrate the consistency of everyday reliability when in operation. A lidar provider must have a track record of developing reliable products that can withstand shock, vibration, and other factors – and manufacturing them in volume with low defects. For example, Velodyne Lidar has achieved certification to the ISO 9001:2015 standard, demonstrating its commitment to design and manufacture world-class products compliant with international quality standards.
Commercial Availability. While new technology is exciting to use and integrate, a robotics business will thrive only if their robots can be reliably reproduced. Therefore, mobile robots must be designed with commercially available components that are easy to source and can be purchased in volume. Velodyne’s real-time 3D lidar sensors are built with widely available 905nm lasers and avalanche photodiodes. The established breadth and scale of the supply base for Velodyne’s 905nm lidar components are at least one order of magnitude larger than those utilized in other types of lidar technology. Many of the board- and chip-level electronic components are COTS (Commercial Off-the-Shelf) which helps to reduce price and lead-times on both new sensors and RMA repairs.
Lidar Fuels Expanding Robot Autonomy
“Lidar helps mobile robots navigate within natural environments by performing collision avoidance, object profiling, and identification. This enables robots to better understand both the physical environment they are operating in and changes in their surroundings such as moving people and objects,” said Bertini.
By leveraging lidar technology to support expanding autonomous capabilities, mobile robots will continue to evolve and take on a greater complexity of tasks and work environments.
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