Tag: OpenVLA

The humanoid robotics landscape has split into two competing philosophies. On one side stand vertically integrated, well-funded proprietary labs—such as Tesla (Optimus), Figure AI, 1X Technologies, and Boston Dynamics. These organizations operate on closed-source, full-stack models: proprietary mechanical airframes, custom harmonic and planetary actuators, in-house edge silicon, and closed foundation neural policies trained on massive […]

Classical industrial robotics relies on an explicitly decoupled, modular software pipeline: perception, state estimation, motion planning, inverse kinematics (IK), and joint-level PID control. In this traditional paradigm, camera pixels are reduced to calibrated 3D bounding boxes, an analytical planner evaluates collision-free cubic splines, an inverse kinematics solver computes targeted joint angles, and motor drivers calculate […]

For decades, robotics operated within a rigid, deterministic paradigm. If an industrial automation engineer wanted a robot to pick a steel bolt from a conveyor and thread it into an engine block, they wrote deterministic code: hardcoded 3D Cartesian coordinates, inverse kinematics (IK) solvers, explicit trajectory waypoints, and tightly calibrated bounding-box vision filters. If the […]