Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Calli, Berk"'
In this paper, we present a benchmarking study of vision-based grasp synthesis algorithms, each with distinct approaches, and provide a comparative analysis of their performance under different experimental conditions. In particular, we compare two m
Externí odkaz:
http://arxiv.org/abs/2307.11622
The automation of key processes in metal cutting would substantially benefit many industries such as manufacturing and metal recycling. We present a vision-based control scheme for automated metal cutting with oxy-fuel torches, an established cutting
Externí odkaz:
http://arxiv.org/abs/2307.00133
Autor:
Bashkirova, Dina, Mishra, Samarth, Lteif, Diala, Teterwak, Piotr, Kim, Donghyun, Alladkani, Fadi, Akl, James, Calli, Berk, Bargal, Sarah Adel, Saenko, Kate, Kim, Daehan, Seo, Minseok, Jeon, YoungJin, Choi, Dong-Geol, Ettedgui, Shahaf, Giryes, Raja, Abu-Hussein, Shady, Xie, Binhui, Li, Shuang
Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings with high visual diversity, such as waste sorting. In industrial waste sorting, one of the biggest challenges is the e
Externí odkaz:
http://arxiv.org/abs/2303.14828
Autor:
Dasari, Sudeep, Wang, Jianren, Hong, Joyce, Bahl, Shikhar, Lin, Yixin, Wang, Austin, Thankaraj, Abitha, Chahal, Karanbir, Calli, Berk, Gupta, Saurabh, Held, David, Pinto, Lerrel, Pathak, Deepak, Kumar, Vikash, Gupta, Abhinav
Benchmarks offer a scientific way to compare algorithms using objective performance metrics. Good benchmarks have two features: (a) they should be widely useful for many research groups; (b) and they should produce reproducible findings. In robotic m
Externí odkaz:
http://arxiv.org/abs/2203.08098
Publikováno v:
IEEE Robotics and Automation Letters, vol. 7, no. 3, pp. 5866-5873, July 2022
Benchmarking of robotic manipulations is one of the open issues in robotic research. An important factor that has enabled progress in this area in the last decade is the existence of common object sets that have been shared among different research g
Externí odkaz:
http://arxiv.org/abs/2111.01527
Publikováno v:
In Journal of Cleaner Production 10 September 2024 470
This paper discusses recent research progress in robotic grasping and manipulation in the light of the latest Robotic Grasping and Manipulation Competitions (RGMCs). We first provide an overview of past benchmarks and competitions related to the robo
Externí odkaz:
http://arxiv.org/abs/2108.01483
Autor:
Bashkirova, Dina, Abdelfattah, Mohamed, Zhu, Ziliang, Akl, James, Alladkani, Fadi, Hu, Ping, Ablavsky, Vitaly, Calli, Berk, Bargal, Sarah Adel, Saenko, Kate
Less than 35% of recyclable waste is being actually recycled in the US, which leads to increased soil and sea pollution and is one of the major concerns of environmental researchers as well as the common public. At the heart of the problem are the in
Externí odkaz:
http://arxiv.org/abs/2106.02740
We present an ensemble learning methodology that combines multiple existing robotic grasp synthesis algorithms and obtain a success rate that is significantly better than the individual algorithms. The methodology treats the grasping algorithms as "e
Externí odkaz:
http://arxiv.org/abs/2105.00329
Autor:
Liu, Ziyuan, Liu, Wei, Qin, Yuzhe, Xiang, Fanbo, Gou, Minghao, Xin, Songyan, Roa, Maximo A., Calli, Berk, Su, Hao, Sun, Yu, Tan, Ping
Publikováno v:
IEEE Robotics and Automation Letters, 2021
In this paper, we propose a cloud-based benchmark for robotic grasping and manipulation, called the OCRTOC benchmark. The benchmark focuses on the object rearrangement problem, specifically table organization tasks. We provide a set of identical real
Externí odkaz:
http://arxiv.org/abs/2104.11446