Company: OTSA
Filing Date: 2025-07-07
Form Type: F-1/A
Source: 0001213900-25-061733
Chunk: 170

Company: OTSAW Ltd
Filing Date: 2025-07-07
Form: F-1/A
Chunk 170
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 powered by four of our core multi -layeredtechnologies that we have developed and continue to enhance, including: 3D Simultaneous Localization and Mapping (“3D SLAM”) Technology. Our patented 3D SLAM technology is central to our core outdoor autonomy and robotic software competencies. The 3D SLAM technology enables our AMRs to build a 3D map and navigate accurately and safely through an unfamiliar, unstructured, and challenging environment while simultaneously identifying their own locations. Using the sensory data obtained by sensors managed by our proprietary sensor fusion technology (“Sensor Fusion”), the 3D SLAM software interprets the environmental measurements based on a series of patented interlacing algorithms and scan -matchingtechniques. It identifies landmarks, markers and signs within an unknown environment, and determines the AMRs’ position relative to those markers and continues to interpret additional data within the designated area until it has enough reference points to create a comprehensive map of the area. Using this method, a SLAM -enableddevice can create highly accurate 3DD models and maps of its surroundings and seamlessly position itself at any point in time. Sensor Fusion Technology Our AMRs are equipped with various advanced sensors, such as 3D LiDAR scanners, sonar, GPS, Inertial Measurement Unit (IMU) sensors, and 2D and 3D cameras. However, each sensor has its unique strengths and weaknesses. For example, 3D LiDAR enables precise 3D object detection with range accuracy and free space detection ability, but lacks a range of cameras or radar. Similarly, radar and sonar can accurately determine distance and object movement even in challenging weather conditions but cannot identify and classify objects such as pedestrians, bicyclists or other passing vehicles. 3D and 2D cameras enable an AMR to identify and classify objects, detect the object’s angular position and 103 scene context. However, these cameras may easily be blinded by dirt, sun -flares, rain, snow or darkness. Our AMRs also utilize IMU sensors, such as accelerometers, gyroscopes, magnetometers, and barometers to track the AMR’s movement and approximate location. However, IMU sensors are vulnerable to drifts, biases and external -environmenterrors, and are less accurate in determining the AMR’s exact location. GPS provides concise latitude, longitude and altitude information, but its application is limited in GPS -deniedareas such as indoor areas, tunnels and other unchartered landscapes. Lastly,