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Title | Robot Motor Intelligence (RoMI) Lab - Heriot-Watt |
Description | The Robot Motor Intelligence (RoMI) Lab focuses on legged robotics, optimization and AI. We are part of Edinburgh Centre for Robotics at Heriot-Watt |
Keywords | N/A |
WebSite | romilab.org |
Host IP | 34.159.137.246 |
Location | United States |
Site | Rank |
US$247,569
Last updated: 2023-05-19 19:54:11
romilab.org has Semrush global rank of 42,753,022. romilab.org has an estimated worth of US$ 247,569, based on its estimated Ads revenue. romilab.org receives approximately 28,566 unique visitors each day. Its web server is located in United States, with IP address 34.159.137.246. According to SiteAdvisor, romilab.org is safe to visit. |
Purchase/Sale Value | US$247,569 |
Daily Ads Revenue | US$229 |
Monthly Ads Revenue | US$6,856 |
Yearly Ads Revenue | US$82,269 |
Daily Unique Visitors | 1,905 |
Note: All traffic and earnings values are estimates. |
Host | Type | TTL | Data |
romilab.org. | A | 20 | IP: 34.159.137.246 |
romilab.org. | A | 20 | IP: 3.125.16.34 |
romilab.org. | NS | 3600 | NS Record: dns2.p02.nsone.net. |
romilab.org. | NS | 3600 | NS Record: dns3.p02.nsone.net. |
romilab.org. | NS | 3600 | NS Record: dns4.p02.nsone.net. |
romilab.org. | NS | 3600 | NS Record: dns1.p02.nsone.net. |
Toggle navigation Robot Motor Intelligence (RoMI) Lab Home Team Research Robots News --> Publications Joining Previous Next About the RoMI Lab How the robots could develop their motor intelligence? We have seen a remarkable evolution in robotics such as the Atlas robot performing gymnastics routines. However, despite the progress, these behaviors are typically scripted or generated using domain-specific knowledge. These methods highly rely on static models and human’s intuition that limit its application to a broader domain. Furthermore, recent advance in deep learning has shown impressive results, but unfortunately, it builds a narrow intelligence that cannot be transferred to different circumstances. This kind of intelligence is not reliable and cannot be robustly generalized in motor control. Indeed, it is naively approached as a ‘‘universal’’ function approximator, and the lack of building abstract concepts affects its generalization. In our group, we focus on creating motor |
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