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StartLux: Post-test Control Board Sorting Simulation

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Choose the next board and destination as assembly priorities and quality-release states change.

by admin · listed 10 hours ago

⚡ What System1 does here

StartLux chooses which board to pick next and where to place it using structured inventory, quality-release, line-demand and robot-state data. The harness filters compatible destinations, executes grasping and placement, rejects stale choices and verifies physical completion. The model does not inspect board images or perform electrical tests.

About

Two assembly lines need compatible control and interface boards, but a main batch is held for a quality exception and a retest batch must be released before use. This simulation places StartLux Decision between the production context and an existing robot skill library: decide which item to handle next, then select a valid destination. The recording shows a Panda arm first supplying line B, then completing line A with released material, and finally placing the exceptional main-batch board in a quarantine tray. The final screen confirms both supply groups are complete and the exceptional board is isolated. Candidate actions and the selected option appear alongside the moving arm. According to the accompanying implementation notes, StartLux receives structured board type, batch, simulated quality-release status, line shortage and current grasp/placement state. It selects a board, a compatible supply position, a buffer or quarantine destination, or a pause. While one skill is executing, the next choice may be prepared; the harness still waits for a stable grasp or completed placement before handing over. Changed quality status or occupied destinations can invalidate a prepared choice. The useful pattern is coordinated production sequencing with feedback: choosing a destination is only one step, and the program must confirm that the board is physically supported and the gripper has withdrawn before counting the job as complete. Evidence and limits: this is a user-supplied MuJoCo simulation recording, reviewed with its accompanying documentation. The modeled parts are rigid packaged-board substitutes; quality-test outcomes are simulated inputs, not measurements of real circuit boards. No simulation was rerun and no original API trace or physical robot was independently tested for this listing. On-screen probabilities indicate action preference, not task success rates. The preserved video has Chinese interface text and no audio.

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