Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Tianrui Guan"'
Autor:
Tianrui Guan, Divya Kothandaraman, Rohan Chandra, Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Dinesh Manocha
Publikováno v:
IEEE Robotics and Automation Letters. 7:8138-8145
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e0f2ceb4e3b2fe0f93b7e617cc9797b
https://doi.org/10.1109/lra.2022.3187278
https://doi.org/10.1109/lra.2022.3187278
We present a terrain traversability mapping and navigation system (TNS) for autonomous excavator applications in an unstructured environment. We use an efficient approach to extract terrain features from RGB images and 3D point clouds and incorporate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e8551c7ae78e19de023fb4a49123ce0f
https://doi.org/10.21203/rs.3.rs-2646589/v2
https://doi.org/10.21203/rs.3.rs-2646589/v2
We present a terrain traversability mapping and navigation system (TNS) for autonomous excavator applications in an unstructured environment. We use an efficient approach to extract terrain features from RGB images and 3D point clouds and incorporate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c09be6a1f4959c5650c209137f58e2b
https://doi.org/10.21203/rs.3.rs-2646589/v1
https://doi.org/10.21203/rs.3.rs-2646589/v1
Autor:
Trisha Mittal, Tianrui Guan, Dinesh Manocha, Uttaran Bhattacharya, Srujan Panuganti, Rohan Chandra, Aniket Bera
Publikováno v:
IEEE Robotics and Automation Letters. 5:4882-4890
We present a novel approach for traffic forecasting in urban traffic scenarios using a combination of spectral graph analysis and deep learning. We predict both the low-level information (future trajectories) as well as the high-level information (ro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3cb87877e60ae3a4ffc2ad60e1c2074a
https://doi.org/10.1109/lra.2020.3004794
https://doi.org/10.1109/lra.2020.3004794
We present a novel outdoor navigation algorithm to generate stable and efficient actions to navigate a robot to reach a goal. We use a multi-stage training pipeline and show that our approach produces policies that result in stable and reliable robot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55b829f4503a259d2817d6b6089126f3
We present a terrain traversability mapping and navigation system (TNS) for autonomous excavator applications in an unstructured environment. We use an efficient approach to extract terrain features from RGB images and 3D point clouds and incorporate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f92aa6696ae5ef604437d62b074a804b
Autor:
Tianrui Guan, Jing Liang, Dinesh Manocha, Rohan Chandra, Adarsh Jagan Sathyamoorthy, Utsav Patel
Publikováno v:
ICRA
We present DenseCAvoid, a novel navigation algorithm for navigating a robot through dense crowds and avoiding collisions by anticipating pedestrian behaviors. Our formulation uses visual sensors and a pedestrian trajectory prediction algorithm to tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::461a27ca093d7329c4373fe2216483aa
https://doi.org/10.1109/icra40945.2020.9197379
https://doi.org/10.1109/icra40945.2020.9197379
We present a modified velocity-obstacle (VO) algorithm that uses probabilistic partial observations of the environment to compute velocities and navigate a robot to a target. Our system uses commodity visual sensors, including a mono-camera and a 2D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25266fbe0c1ea52c4e13cae833733aa5
http://arxiv.org/abs/2004.10976
http://arxiv.org/abs/2004.10976
Publikováno v:
Journal of Alloys and Compounds. 740:844-851
High-quality vanadium dioxide (VO2) thermochromic thin films were fabricated on ZnO/soda-lime glass via direct current magnetron sputtering at a low temperature of 320 °C. The ZnO polycrystalline film was used as a buffer layer between glass substra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::920d179a675b864e57739d015e552336
https://doi.org/10.1016/j.jallcom.2018.01.066
https://doi.org/10.1016/j.jallcom.2018.01.066