Robot Whole-Body Control: Contacts, Tasks, Momentum and Constraints
Understand robot whole-body control through contacts, task priorities, momentum, constraints, optimization, learned commands and validation.
English articles about robot data and hardware at Physical AI Lab.
Understand robot whole-body control through contacts, task priorities, momentum, constraints, optimization, learned commands and validation.
Compare robot motion planning and trajectory optimization by search, initialization, collision, costs, dynamics, timing and feedback execution.
Compare inverse kinematics and inverse dynamics by inputs, outputs, constraints, singularities, torque limits, contact and feedback control.
Separate robot reducer backlash, lost motion, hysteresis and torsional stiffness and compare them with a controlled torque-angle test.
Understand robot motor driver architecture including DC bus, inverter, gate drivers, current sensing, control MCU, protection and regeneration.
Compare series elastic and quasi-direct-drive actuators by force sensing, backdrivability, bandwidth, impacts, thermal duty and validation.
Understand field-oriented control for robot motors, including phase current, rotor angle, d-q axes, PI control, PWM, limits and torque validation.
Understand robot joint backdrivability by reduction ratio, reflected inertia, friction, motor electrical state, active control and output tests.
Compare robot actuator torque density by peak and continuous output, mass, volume, transmission, cooling, speed and measured duty cycle.
Compare robot gripper types including parallel, vacuum, soft and dexterous designs by object range, sensing, failure modes and cycle tests.