Monitor robotic simulation task progress and success from RGB video frames.
npx skills add https://github.com/bensonlee5/openral --skill robometer-4b
Please help me install this Agent Skill. Skill: robometer-4b Source: https://github.com/bensonlee5/openral/tree/main/rskills/robometer-4b Command: npx skills add https://github.com/bensonlee5/openral --skill robometer-4b
This Skill provides real-time monitoring of task progress and success during robotic simulations, enabling adaptive planning and decision-making.
Install the rskill-robometer-4b-nf4 to monitor progress during robot simulations.
High-intent search queries and answers about installing and using this skill.
Task success prediction in robotics processes real-time video frames and text instructions to estimate the probability of task completion at each frame, enabling early replanning during simulation execution.
You monitor task progress in robotic simulations by processing real-time RGB video streams and text instructions, which normalizes per-frame progress and outputs continuous success likelihood feedback.
You need the OpenRAL runtime and the Robometer-4B model installed to process RGB camera streams and text instructions for continuous task progress feedback.
Yes, you can use this Skill for adaptive task planning because it provides continuous per-frame success probability feedback, allowing the system to decide when to replan or take action during simulation.
The best way to predict robot task success probability per frame is to process real-time RGB camera streams and text instructions via the Robometer-4B model within the OpenRAL runtime environment.
Task success prediction requires RGB camera streams and text instructions because the Robometer-4B model processes both inputs together to normalize progress and estimate success likelihood during robotic simulations.
bensonlee5Execute robotic manipulation tasks from natural language descriptions using a Sawyer robot.
EthansuttorGenerate adaptive GOAP action sequences for complex objectives.
bensonlee5Verify robotic task success by comparing action results with scene and reward queries.
bensonlee5Monitor robotic task progress with Qwen3-VL-4B VLM zero-shot reward model.
