The Experts below are selected from a list of 83364 Experts worldwide ranked by ideXlab platform
Masayuki Inaba - One of the best experts on this subject based on the ideXlab platform.
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autonomous 3d walking system for a humanoid robot based on visual step recognition and 3d foot step planner
International Conference on Robotics and Automation, 2005Co-Authors: Kei Okada, T Ogura, A Haneda, Masayuki InabaAbstract:This paper describes vision-based 3D walking system of a humanoid robot by combining a precise 3D Planar Surface detection method and a practical 3D footstep planner method. The walking control system requires vision system with 10[mm] accuracy. Then we developed the precise 3D Planar Surface recognition system by combining the 3D Hough transformation method and the robust estimation method. We also developed practical 3D foot step planner by considering kinematics and dynamics restriction of robot hardware. Finally, we realized vision based 3D walking experiments that a humanoid robot steps upon an unknown obstacle are shown.
Henrik I Christensen - One of the best experts on this subject based on the ideXlab platform.
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Planar Surface slam with 3d and 2d sensors
International Conference on Robotics and Automation, 2012Co-Authors: Alexander J B Trevor, John G Rogers, Henrik I ChristensenAbstract:We present an extension to our feature based mapping technique that allows for the use of Planar Surfaces such as walls, tables, counters, or other Planar Surfaces as landmarks in our mapper. These Planar Surfaces are measured both in 3D point clouds, as well as 2D laser scans. These sensing modalities compliment each other well, as they differ significantly in their measurable fields of view and maximum ranges. We present experiments to evaluate the contributions of each type of sensor.
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ICRA - Planar Surface SLAM with 3D and 2D sensors
2012 IEEE International Conference on Robotics and Automation, 2012Co-Authors: Alexander J B Trevor, John G Rogers, Henrik I ChristensenAbstract:We present an extension to our feature based mapping technique that allows for the use of Planar Surfaces such as walls, tables, counters, or other Planar Surfaces as landmarks in our mapper. These Planar Surfaces are measured both in 3D point clouds, as well as 2D laser scans. These sensing modalities compliment each other well, as they differ significantly in their measurable fields of view and maximum ranges. We present experiments to evaluate the contributions of each type of sensor.
Avideh Zakhor - One of the best experts on this subject based on the ideXlab platform.
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Watertight Planar Surface Meshing of Indoor Point-Clouds with Voxel Carving
2013 International Conference on 3D Vision - 3DV 2013, 2013Co-Authors: Eric Turner, Avideh ZakhorAbstract:3D modeling of building architecture from point-cloud scans is a rapidly advancing field. These models are used in augmented reality, navigation, and energy simulation applications. State-of-the-art scanning produces accurate point-clouds of building interiors containing hundreds of millions of points. Current Surface reconstruction techniques either do not preserve sharp features common in a man-made structures, do not guarantee water tightness, or are not constructed in a scalable manner. This paper presents an approach that generates watertight triangulated Surfaces from input point-clouds, preserving the sharp features common in buildings. The input point-cloud is converted into a voxelized representation, utilizing a memory-efficient data structure. The triangulation is produced by analyzing Planar regions within the model. These regions are represented with an efficient number of elements, while still preserving triangle quality. This approach can be applied to data of arbitrary size to result in detailed models. We apply this technique to several data sets of building interiors and analyze the accuracy of the resulting Surfaces with respect to the input point-clouds.
Kei Okada - One of the best experts on this subject based on the ideXlab platform.
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autonomous 3d walking system for a humanoid robot based on visual step recognition and 3d foot step planner
International Conference on Robotics and Automation, 2005Co-Authors: Kei Okada, T Ogura, A Haneda, Masayuki InabaAbstract:This paper describes vision-based 3D walking system of a humanoid robot by combining a precise 3D Planar Surface detection method and a practical 3D footstep planner method. The walking control system requires vision system with 10[mm] accuracy. Then we developed the precise 3D Planar Surface recognition system by combining the 3D Hough transformation method and the robust estimation method. We also developed practical 3D foot step planner by considering kinematics and dynamics restriction of robot hardware. Finally, we realized vision based 3D walking experiments that a humanoid robot steps upon an unknown obstacle are shown.
Alexander J B Trevor - One of the best experts on this subject based on the ideXlab platform.
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Planar Surface slam with 3d and 2d sensors
International Conference on Robotics and Automation, 2012Co-Authors: Alexander J B Trevor, John G Rogers, Henrik I ChristensenAbstract:We present an extension to our feature based mapping technique that allows for the use of Planar Surfaces such as walls, tables, counters, or other Planar Surfaces as landmarks in our mapper. These Planar Surfaces are measured both in 3D point clouds, as well as 2D laser scans. These sensing modalities compliment each other well, as they differ significantly in their measurable fields of view and maximum ranges. We present experiments to evaluate the contributions of each type of sensor.
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ICRA - Planar Surface SLAM with 3D and 2D sensors
2012 IEEE International Conference on Robotics and Automation, 2012Co-Authors: Alexander J B Trevor, John G Rogers, Henrik I ChristensenAbstract:We present an extension to our feature based mapping technique that allows for the use of Planar Surfaces such as walls, tables, counters, or other Planar Surfaces as landmarks in our mapper. These Planar Surfaces are measured both in 3D point clouds, as well as 2D laser scans. These sensing modalities compliment each other well, as they differ significantly in their measurable fields of view and maximum ranges. We present experiments to evaluate the contributions of each type of sensor.
