This content is not included in your SAE MOBILUS subscription, or you are not logged in.
The Benefits of Advanced 3D Lidar for Autonomous Mobile Robots
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 15, 2021 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Breakthroughs in automation and robotics are already improving worker safety and efficiency, and these benefits will continue to grow as autonomous mobile robots (AMRs) become capable of performing increasingly complex tasks. Improvements in mobile robots’ performance capabilities will be driven largely by increased utilization of more advanced sensor and software technologies. Next generation sensors, such as advanced 3D lidar, will increase AMRs’ abilities to monitor and respond to their changing surroundings in both indoor and outdoor applications. These improvements are critical for achieving broad AMR adoption because robots must detect and classify objects at ranges that allow appropriate decision-making and safe, efficient navigation. This requires perception data detailed enough to support the robot’s ability to identify and distinguish between objects of varying motion, shape, reflectivity, and material composition. Advanced AMRs also require precise localization and mapping capabilities in order to know exactly where they are in relation to their surroundings. Sensor data that can be efficiently processed, transmitted and stored can facilitate smooth development of this situational awareness. Further, AMR sensors must perform well in broad temperature and environmental ranges, without placing excessive strain on the robot’s battery system. With these requirements in mind, we can clearly recognize the benefits of integrating advanced 3D lidar technology in a range of AMR applications.
CitationGradu, M., "The Benefits of Advanced 3D Lidar for Autonomous Mobile Robots," SAE Technical Paper 2021-01-1015, 2021, https://doi.org/10.4271/2021-01-1015.
Data Sets - Support Documents
|Unnamed Dataset 1|
- Langmann , B. , Hartmann , K. , and Loffeld , O. Depth Camera Technology Comparison and Performance Evaluation ICPRAM (2) 2012 Keselman , L. et al. Intel RealSense Stereoscopic Depth Cameras CVPR 2017