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Plug-and-play collision avoidance module for ROS1 and ROS2

Hacker News

Plug-and-play collision avoidance module for ROS1 and ROS2

3Laws Supervisor is a ROS package designed for easily adding real-time collision avoidance capabilities to an existing stack. It works for robots operating in either autonomous or teleop modes. We're currently looking for feedback from the community so you can download it for free! It's available as a ROS1 (noetic) and ROS2 (foxy/galactic/humble/iron) package, running on x86-64 and arm64 architectures. We hope it can help with your development efforts. Sincerely, The 3Laws Team

Visit product View on Hacker NewsMay 21, 2024

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63%63% 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.

Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released

55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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