Motion Tracking—the Secret Weapon in Autonomous Navigation?
Guest Blog by Zachary Steck, Market Specialist for AGV/AMR from MHI Member Company, Pepperl+Fuchs, Inc.
As autonomous mobile robots (AMRs) become more prevalent in industrial automation, having the right tools available to ensure that these bots can safely and efficiently navigate through a warehouse is of paramount importance. For many years, LiDAR has been the flagship of autonomous navigation and the main component in determining precise positions, such as when an automated forklift steers through the aisles of a warehouse. Behind the scenes, however, there are many other sensor technologies that support this process, many of which can be described as motion tracking.
Motion tracking provides data from motion-based sensors that can be used to estimate changes in position over time. While LiDAR remains a key aspect in AMR movement, motion tracking could be used in combination with scanners to add additional layers of condition monitoring and preventive safety. There is a wide range of powerful technologies on the market that guarantee the highest precision in navigation and guidance. Mobile autonomous vehicles can definitely benefit from combining these technologies to achieve the optimal machine design. This ensures that mobile robots can operate safely, effectively, and efficiently.
Let’s take a closer look at what sensing options are available and which applications can be solved using motion tracking devices. For motion tracking, there are both very simple and highly complex sensing solutions that cover a wide array of detection applications. Below are the goals and solution descriptions of some of these applications …
The Goal: Direction detection systems ensure that the vehicle is oriented in the correct direction of travel after starting up. They must provide essential information to the vehicle control system so that the vehicle can be steered safely and maintain a stable course, regardless of the weight and size of the load. The direction detection must be reliable and safe, while remaining unaffected by environmental influences. This is particularly important after vehicle initialization or during reference runs to verify the direction of travel.
The Solution: Inductive safety sensors deliver reliable data for direction detection. This data is generated by safe position monitoring of the switching cams on each steering axle of the AMR. The sensor detects the metal target – the switching cam – and transmits the corresponding switching signal to the control system. This prevents excessive steering angles, for example when transporting heavy loads. The sensors are able to detect the target without dead band, meaning no minimum distance is required. Detection is also not impaired by dust and dirt.
The Goal: Transport operations should be carried out as quickly as possible and the respective destinations reliably approached. Since obstacles can occur and the environment is often subject to constant change, fast flexibility and responsiveness are required when navigating the transport route. The vehicles and robots must be able to follow the instructions of the controller when driving straight ahead and when cornering. The sensors must self-monitor the location of the vehicle to provide precise position data at all times.
The Solution: While optical sensors perform the task of spatial orientation, autonomous vehicles require additional data to determine their own position accurately. To improve position determination, two measuring systems can be combined. For example, a rotary encoder and 2-D laser scanner. To reliably compensate for measurement tolerances and deviations, rotary encoders are mounted on the wheels of the vehicle. Exact position data can be derived from the precise measurement of the rotational speed. Rotary encoders have a very high resolution, are compact, and cost-effective, making them the ideal choice for vehicle position monitoring applications.
Solution Two: Inertial measurement units (IMUs) detect deviations from straight-line movement with high accuracy by measuring the Coriolis force with a capacitive MEMS sensor. It outputs the rotation rate values (degrees/second) of the corners traveled by the vehicle, providing the additional data needed for dynamic position detection and precise navigation. In addition, the IMU sensor supplies an inclination value to determine the horizontal position of the vehicle in space, as well as acceleration values for multiple axes. These values serve as a further source of information for the AMR controller. For example, a defined maximum steering angle value can be used to prevent the vehicle from tipping over when cornering.
Navigation applications are becoming more complicated by the day, especially with the increasing use of collaborative robots. This leads to additional complexity, as the safety of workers who regularly come into direct contact with these machines must now also be taken into account. The more data you have about your autonomous mobile robot, the easier it will be to determine its exact position in the plant and avoid unnecessary accidents on the floor. For this reason, motion tracking is the secret weapon in autonomous navigation.
