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次ã®æã«åºã¥ããŠè³ªåãã | Abstract: In order to achieve autonomous navigation for low-cost quadcopter, it is essential to solve the challenges of localization and obstacle avoidance. In this study, we evaluated the performance of our proposed system that employs a monocular camera-based visual odometry algorithm for localization and LiDAR sensor for obstacle detection. The experiments conducted show that the proposed system is able to achieve accurate localization and effective obstacle avoidance in various indoor and outdoor environments. In addition, we also conducted experiments to evaluate the computational efficiency of our system, which showed that the proposed method is computationally efficient and suitable for implementation on low-cost embedded hardware. | 1. What challenges need to be solved for achieving autonomous navigation for low-cost quadcopter?
2. What methods were used in the proposed system for localization and obstacle detection?
3. Were the experiments conducted in various indoor and outdoor environments successful?
4. Was the proposed method computationally efficient according to the experiments?
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