Company: OTSA
Filing Date: 2025-01-28
Form Type: DRS
Source: 0001213900-25-007614
Chunk: 149

Company: OTSAW Ltd
Filing Date: 2025-01-28
Form: DRS
Chunk 149
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, 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 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, due to the different rates and frequencies at which sensor data arrives to the processor from the sensor and the intrinsic and external environment -drivensensor biases, sensor synchronization requires a high degree of calibration. 93 Our proprietary Senor Fusion technology is developed to manage, fuse, calibrate, and integrate these sensors installed on our AMRs. Through our proprietary Sensor Fusion algorithms, we are able to harness the strengths of each sensor to achieve autonomous navigation and obstacle avoidance motions. Our proprietary Sensor Fusion algorithms do so by synthesizing the sensory data from all sensors on the AMR and analyzing the data into a unified whole in real -time, mimicking human senses and perceptions. By merging the sensory data into one measurement instead of using singular values provided by each sensor, the sensors are able to complement one another, hence enhancing the accuracy, precision, spatial coverage, or time duration of the AMRs. The Sensor Fusion technology not only reduces uncertainty in machine perception for better decision -makingcapabilities, but it also provides a comprehensive environmental model for the AMRs to determine their most accurate positions relative to obstacles and terrain. This technology ultimately enables our AMRs to operate independently, accurately, reliably, and safely in any environment. Machine Perception Technology and Machine AI-Learning Technology The multi -layeredsynergy of our advanced sensors and cameras, 3D -SLAMtechnology, and Sensor Fusion software enables our AMRs