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[OpenSource] Your iPhone is a robotics data collection/streaming device

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[OpenSource] Your iPhone is a robotics data collection/streaming device

We developed an open-source iPhone application that can collect and stream data from the iPhone’s sensory suite. Download it from the app store and try recording some data yourself! https://apps.apple.com/us/app/anysense/id6742254654 Specifically, we enable streaming and collection of: - RGB, depth and movement data - Audio data from internal or external microphones - External sensor data streamed over Bluetooth The gold star here is for apps like AnySense to help scale robotic data collection the same way that smartphones helped scale vision and language data. With data scaling, we can do some cool stuff like training visuotactile policies on human-collected data that we can directly deploy on the robot! Check out our demo video on our website! If you're interested, contribute to our project on Github. Github: https://github.com/NYU-robot-learning/AnySense

Visit productView on Hacker NewsFeb 26, 2025
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, open · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps, video, way · Missing: mobile apps, ios, personal
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio, smart · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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