Aloha
Related papers: 9
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ALOHA (A Low-cost Open-source Hardware System for Bimanual Teleoperation) is a robotic hardware and learning platform designed to enable dexterous, two-armed manipulation tasks at accessible price points. Developed to democratize robot learning research, ALOHA provides a physical system through which human operators can demonstrate complex manipulation behaviors via teleoperation, generating training data for imitation learning algorithms. These demonstrations allow robots to learn challenging tasks — such as cooking, tool use, and household chores — that require coordinated use of both arms simultaneously. Extensions like Mobile ALOHA expand the platform's capabilities by integrating locomotion, enabling whole-body mobile manipulation in real-world environments. The system matters because high-quality demonstration data is a critical bottleneck in robot learning, and expensive hardware historically limited who could collect it. By offering an open-source, low-cost alternative without sacrificing dexterity, ALOHA has significantly accelerated research into imitation learning, reinforcement learning, and generalist robot policies, making advanced manipulation research accessible to a broader community of engineers and researchers.
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Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation
Zipeng Fu, Tony Z. Zhao, Chelsea Finn
Citations: 28 • 2024
Underwater Wireless Communications for Cooperative Robotics with UWSim-NET
Diego Centelles, Antonio Soriano, José V. Martí, R. Marı́n, Pedro J. Sanz
Citations: 26 • 2019
Effective anti-collision algorithms for RFID robots system
Honggang Wang, Shanshan Wang, Jia Yao, Ruoyu Pan, Qiongdan Huang, Hanlu Zhang, Jingfeng Yang
Citations: 11 • 2019
ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation
ALOHA Team, Jorge Aldaco, Travis Armstrong, Robert Baruch, Jeff Bingham, Sanky Chan, Kenneth Draper, Debidatta Dwibedi, Chelsea Finn, Pete Florence, Spencer Goodrich, Wayne Gramlich, Torr Hage, Alexander Herzog, Jonathan Hoech, Thinh Nguyen, Ian Storz, Baruch Tabanpour, Leila Takayama, Jonathan Tompson, Ayzaan Wahid, Ted Wahrburg, Sichun Xu, Sergey Yaroshenko, Kevin Zakka, Tony Z. Zhao
Citations: 8 • 2024
A waypoint navigation method with collision avoidance using an artificial potential method on random priority
Yuichi Yaguchi, Kyota Tamagawa
Citations: 6 • 2020
Fast tag identification for mobile RFID robots in manufacturing environments
Honggang Wang, Ruixue Yu, Ruoyu Pan, Mengyuan Liu, Qiongdan Huang, Jingfeng Yang
Citations: 6 • 2021
ALOHA: Adapting Local Spatio-Temporal Context to Enhance the Audio-Visual Semantic Segmentation
Yanghao Zhou, Heyan Huang, Cunhan Guo, Rong-Cheng Tu, Zeyu Xiao, Bo Wang, Xian-Ling Mao
Citations: 2 • 2025
Leveraging Single and Multi-task Reinforcement Learning Algorithms for Autonomous Mobile Aloha Robot
Aditya Narendra, D. A. Makarov, Aleksandr I. Panov
Citations: 2 • 2024
ALOHA Unleashed: A Simple Recipe for Robot Dexterity
Tony Z. Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Kamyar Ghasemipour, Chelsea Finn, Ayzaan Wahid
Citations: 2 • 2024