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Autonomous Well Logging Robot with Passive Locomotion |
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Huseyin Rahmi Seren, Erjola Buzi, Max Deffenbaugh(Aramco Services Company, United States) |
| The space and environment within oil wells pose challenges for downhole robots with regards to their shape, energy storage, and locomotion. In this paper, we investigate how to use potential energies from gravity and buoyancy to passively move a robot within a well and avoid obstacles. This approach allows miniaturization by eliminating energy storage and actuators needed for active locomotion. |
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Radar based Obstacle Detection System for Autonomous Unmanned Surface Vehicles |
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Jeesoo Ha, Soo-Ri Im, Woong-Ki Lee, Dong-Hoon Kim, Jae-Kwan Ryu(LIGNex1, Korea) |
| This paper proposes a dynamic obstacle detection system for USV based on marine radar and Electronic Navigational chart (ENC), the most common navigation sensors on ships. In this system, we generated two types of grid maps: one is plan position indicator (PPI) images from marine radar, the other is a hull information-based grid map extracted from ENC. By accumulating the two grid map images, obstacles that appear repeatedly are classified as fixed obstacles, and obstacles that move as the grid map is updated are classified as dynamic obstacles. This system has the advantage of enabling simple obstacle recognition without the need to additionally mount expensive equipment. |
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Object Detection and Tracking System with Improved DBSCAN Clustering using Radar on Unmanned Surface Vehicle |
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Soori Im(LIGNex1, Korea), Donghoon Kim(LIGNex1 Company, Korea), Hoiyoung Cheon(Hanyang University, Korea), Jaekwan Ryu(LIGNex1 Company, Korea) |
| Unmanned Surface Vehicle(USV) is a promising solution for missions that happened on the ocean such as patrolling, rescuing. It is necessary to detect obstacles for autonomous navigation. However, marine radar has some limitations, which is normally used for USV. This paper proposes an algorithm which is for detecting close obstacles with FMCW radar using the clustering method. Using radar data, the algorithm computes representative clusters and track the clusters with the Nearest Neighbor algorithm. This paper also shows the field experiment result of the proposed algorithm with USV. |
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Numerical Study on Maneuvering Simulation in Waves of USV Using Two-Time-Scale Method |
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Hyeon Kyu Yoon, Thanh Diep Thi Nguyen(Changwon National University, Korea), Minh Van Nguyen(University of Danang - University of Science and Technology, Viet Nam) |
| 1) I corrected following the reviewer’s comment.
2) I replaced all “Two-time scale” into two-time scale.
3) I added and corrected sentences in CONCLUSION;
4,7,9) Thank you. But I don’t agree that there should be any sentences between Chapter 2 and section 2.1, because Chapter 2 includes just sections.
5) Thank you. In general, when describing the name of coordinate system, axes should not be necessary to be subscripts. I changed Oxy in O-xy.
12) I added one more paragraph. |
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