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Xbotics Tutorial Lecture 7: Converting Poses to Gripper Actions

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In Lecture 7 of the "Twenty-One Lectures" series, the Xbotics Embodied Intelligence Lab converts the target object poses obtained in Lecture 6 into gripper actions, using five poses—pre-grasp, grasp, lift, place, and retreat—and a state machine to link the grasp–place closed loop and handle failure recovery. The lab states that teaching simulation can only prove that the program logic closed loop is correct; it cannot replace collision checking, dynamics validation, and real-robot safety testing; the quaternions and distances in the code are for teaching examples only. Its real-robot safety principle requires that AI-generated or AI-modified real-robot code must not be executed directly, and that the real robot must not complete this item through deliberate collision.

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  1. Xbotics Lecture 7: A Robot Manipulation Loop from Target Pose to Grasping, Placement, and Failure Recovery

    In Lecture 7 of the "Twenty-One Lectures" series, the Xbotics Embodied Intelligence Lab converts the target object pose obtained in Lecture 6 into gripper actions, linking the grasp-and-place loop with five poses—pre-grasp, grasp, lift, place, and retreat—and a state machine.

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Planning and decision makingGrasping and manipulationData and simulationSoftware and compute systemsGuides and practice

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