Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

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Session WedBVT6 Gemini 3 Wednesday, October 10, 2012, 09:30–10:30 Mapping II Chair Edwin Olson, Univ. of Michigan Co-Chair 09:30–09:45 WedBVT6.1 Variable reordering strategies for SLAM • We have evaluated existing reordering strategies on standard SLAM datasets. Pratik Agarwal and Edwin Olson Computer Science and Engineering, University of Michigan, USA • We propose an easy to implement reordering algorithm called BHAMD which yields competitive performance. • We provide evidence showing that few gains remain with respect to variants of minimum degree ordering. Reorder and solve time for different reordering algorithms 10:00–10:15 WedBVT6.3 Planar Polygon Extraction and Merging from Depth Images Joydeep Biswas and Manuela Veloso School of Computer Science, Carnegie Mellon University, USA We introduce an approach to building 3D maps of indoor environments modelled as planar surfaces using depth cameras. •Neighborhoods of plane filtered points are extracted from each observed depth image and fitted to convex polygons. •The polygons from each frame are matched to existing map polygons using OpenGL accelerated ray casting. •Matched polygons are then merged over time using sequential update and merging of the scatter matrix of observed polygons. The polygon extraction and merging algorithms take on an average 2.5 ms for each depth image of size 640x480 pixels. Plane Filtered and fitted convex polygons shown in blue from each frame (top) are merged across successive frames to generate complete map (bottom). 10:20–10:25 WedBVT6.5 2D PCA-based Localization for Mobile Robots in Unstructured Environments Fernando Carreira (1) , Camilo Christo (2) , Duarte Valério (2) , Mário Ramalho (2) , Carlos Cardeira (2) , João Calado (1,2) and Paulo Oliveira (3) (1) ADEM / ISEL, Polytechnic Institute of Lisbon, Portugal (2) IDMEC / IST, Technical University of Lisbon, Portugal (3) ISR / IST, Technical University of Lisbon, Portugal • Self-localization system for mobile robots to operate in indoor environment, with only onboard sensors • The database of images stored onboard is of reduced size, when compared with acquired images • No hypothesis is made about specific features in the environment • The localization system estimates in real time the position and slippage with global stable error dynamics. Results of stability tests considering wrong initial position and attitude 09:45–10:00 WedBVT6.2 An Object-Based Semantic World Model for Long- Term Change Detection and Semantic Querying • RGB-D based mapping aboard a localized robot • Uniquely weak perceptual assumptions • Scales to large (1600 m 2 ), long-term (six weeks) operation • Supports change detection and semantic querying • 326 GB dataset available! Julian Mason and Bhaskara Marthi Duke University and Willow Garage 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems –138– Example of semantic query for “medium-sized things in the cafeteria.” 10:15–10:20 WedBVT6.4 Reconfigurable Intelligent Space, R+iSpace, and Mobile Module, MoMo JongSeung Park Graduate School of Sci. and Eng, Ritsumeikan University, Japan Joo-Ho Lee College of Information Sci. and Eng, Ritsumeikan University, Japan • In this video and paper, the new concept of Intelligent space, ‘R+iSpace’ is introduced. • The whole devices in the R+iSpace can rearrange themselves automatically according to situation. • To achieve R+iSpace in real environment, we propose a mobile module, ‘MoMo’. • The devices can move on the wall and the ceiling through mounting on the MoMo. The R+iSpace system and The MoMo 10:25–10:30 WedBVT6.6 Deformable Soft Wheel Robot using Hybrid Actuation Je-sung Koh, Dae-young Lee, Seung-won Kim and Kyu-jin Cho Dept. Mechanical and Aerospace Eng., Seoul National University, South Korea • Multimodal motion ; Three driving modes for penetrating obstacles. • Caterpillar motion : passing through the gap • Wheel driving : fast movement on the ground • Legged wheel motion : climbing the stair • Hybrid actuation system • Deformable wheel : Shape memory alloy coil spring actuator • Wheel driving : DC motor Three driving modes of Deformable wheel robot
Session WedCT1 Pegaso A Wednesday, October 10, 2012, 11:00–12:30 Object Detection and Tracking Chair Co-Chair 11:00–11:15 WedCT1.1 Reliable Object Detection and Segmentation using Inpainting Ji Hoon Joung 1 , M. S. Ryoo 2 Sunglok Choi 3 and Sung-Rak Kim 1 1 Robotics Research Department, Hyundai Heavy Industries, South Korea 2 Mobility and Robotic Systems Section, Jet Propulsion Laboratory, USA 3 Robot Research Department, ETRI, South Korea • This paper presents a novel object detection and segmentation method utilizing an inpainting algorithm. We newly utilize inpainting to judge whether an object candidate region includes the foreground object or not. • The key idea is that if we erase a certain region from an image, the inpainting algorithm is expected to recover the erased image only when it belongs a background area. • We illustrate how our inpainting-based detection / segmentation approach benefits the object detection using two different pedestrian datasets Concept of the proposed method 11:30–11:45 WedCT1.3 Exploiting and modeling local 3D structure for predicting object locations Alper Aydemir and Patric Jensfelt Center for Autonomous Systems, KTH, Sweden • We propose the use of local 3D shape around objects in everyday scenes as a strong indicator of the placement of these objects. We call this the 3D context of an object. • We propose a conceptually simple and effective method to capture this information. • Our results show that 3D contextual information is a strong indicator of object placement in everyday scenes. • An RGB-D data set from five different countries in Europe was collected and used for evaluation. Top figure shows a kitchen scene, and the bottom figure the method’s response for the object cup. 12:00–12:15 WedCT1.5 Fast High Resolution 3D Laser Scanning by Real-Time Object Tracking and Segmentation Jens T. Thielemann, Asbjørn Berge, Øystein Skotheim and Trine Kirkhus SINTEF ICT, Norway E-mail: {jtt,trk,asbe,osk}@sintef.no • This paper presents a real-time contour tracking and object segmentation algorithm for 3D range images. The algorithm is used to control a novel micro-mirror based imaging laser scanner, which provides a dynamic trade-off between resolution and frame rate. The micro-mirrors are controllable, enabling us to speed up acquisition significantly by only sampling on the object that is tracked and of interest. As the hardware is under development, we benchmark our algorithms on data from a SICK LMS100- 10000 laser scanner mounted on a tilting platform. We find that objects are tracked and segmented well on pixel-level; that frame rate/resolution can be increased 3-4 times through our approach compared to scanners having static scan trajectories, and that the algorithm runs in 30 ms/image on a Intel Core i7 CPU using a single core. 11:15–11:30 WedCT1.2 3D Textureless Object Detection and Tracking: An Edge-based Approach Changhyun Choi and Henrik I. Christensen College of Computing, Georgia Institute of Technology, USA Example frames from our detection and tracking results • An approach to textureless object detection and tracking of the 3D pose • Detection and tracking schemes are coherently integrated in a particle filtering framework on the SE(3) • For object detection, an efficient chamfer matching is employed • A set of coarse poses is estimated from the chamfer matching results • Particles are initialized from the coarse pose hypotheses by randomly drawing based on costs of the matching • To ensure the initialized particles are at or close to the global optimum, an annealing process is performed after the initialization • Comparative results for several image sequences with clutter are shown to validate the effectiveness of our approach 11:45–12:00 WedCT1.4 Birth Intensity Online Estimation in GM-PHD Filter for Multi-Target Visual Tracking Xiaolong Zhou, Y.F. Li, Tianxiang Bai and Yazhe Tang Dept. of MBE, City University of Hong Kong, Hong Kong, China Bingwei He Dept. of Mechanical Engineering and Automation, Fuzhou University, China • A multi-target visual tracking system that combines object detection and GM-PHD filter is developed • An improved measurement-dependent birth intensity online estimation method that based on the entropy distribution and the coverage rate is proposed • Entropy distribution based birth intensity update is proposed to remove those Gaussian components like noises within the birth intensity which are irrelevant with the birth measurements • Coverage rate based birth intensity update is proposed to further eliminate the noises 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems –139– Tracking results comparison for data sets PETS 2000 and CAVIAR. (a) Detection results. (b) Tracking results with birth process proposed in [13]. (c) Tracking results with birth process proposed in this paper. 12:15–12:30 WedCT1.6 A Heteroscedastic Approach to Independent Motion Detection for Actuated Visual Sensors Carlo Ciliberto, Sean Ryan Fanello, Lorenzo Natale and Giorgio Metta Robotics Brain and Cognitive Sciences, Istituto Italiano di Tecnologia, Italy • A compositional framework is presented to perform real-time independent motion detection for applications in Robotics. • The algorithm can be easily adapted to a wide range of robotic platforms thanks to the flexibility granted by its modular structure. • The proposed method overcomes the shortcomings of the current state of the art approaches by exploiting the known robot kinematics to predict egomotion rather than relying on vision alone. • A heteroscedastic learning layer is employed to tune the egomotion predictive capabilities of the system. Experiments were conducted on the iCub humanoid robot.
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Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

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