Robotics Glossary
Precise definitions of core humanoid robotics and actuator concepts
Coreless Motor
Learn how coreless motors achieve low inertia and fast response, why dexterous hands use them, and how their size, torque and cooling differ from frameless motors.
Crossed Roller Bearing
Understand how crossed roller bearings support radial, axial and moment loads, and why their stiffness, precision and compact size suit integrated robot joints.
Degrees of Freedom (DoF)
Understand robot degrees of freedom, reachable poses and redundant joints, using the Elf 3 humanoid joint layout to relate mechanical design to motion control.
Dexterous Hand
Compare underactuated and fully actuated robot hands, motor and tendon drive options, and the trade-offs between dexterity, size and control in humanoid manipulation.
Dual Absolute Encoder
Learn why joint motors use input and output absolute encoders, how they measure joint position after reduction, and how the design supports precise closed-loop control.
Embodied AI
Explore embodied AI through the perception, decision and action loop, including humanoid hardware, control systems and real-world data for interacting with the environment.
Force Control (Impedance / Admittance Control)
Compare torque, impedance and admittance control for compliant robot contact, including current-based torque estimates, calibration limits and external force sensors.
Frameless Torque Motor
Discover how frameless stators and rotors integrate into robot joints, reduce redundant housings, and differ in inner- and outer-rotor designs for actuator packaging.
Harmonic Drive (Strain Wave Gear)
Compare harmonic and planetary robot gearboxes by reduction ratio, backlash, stiffness and backdrivability, with selection trade-offs for arms and dynamic leg joints.
Hollow Shaft Motor
Learn how hollow shaft motors route cables and sensor harnesses through robot joints, with design considerations for bore diameter, bearing loads and installation space.
Joint Motor
Explore integrated joint motors, including motors, gearboxes, encoders and drivers, with torque, mass and interface criteria for humanoid and robot-arm selection.
MIT Protocol (CAN Motor Control)
Understand the MIT CAN motor protocol and its position, velocity, feed-forward torque and gain fields, with practical context for hybrid force-position joint control.
Planetary Gearbox
Learn how planetary gearboxes use sun, planet and ring gears for compact torque transmission, and compare their robot-joint trade-offs with harmonic reduction systems.
Quasi-Direct Drive (QDD) Actuator
Explore quasi-direct-drive actuators, low gear ratios, reflected inertia and torque estimation, with backdrivability trade-offs against high-ratio robot joint drives.
RV Reducer (Cycloidal Reducer)
Compare RV cycloidal reducers with harmonic and planetary gears by rigidity, load capacity, mass and shock response for industrial and humanoid robot joint applications.
Reflected Inertia
Understand reflected rotor inertia, its gear-ratio-squared relationship, and why it affects robot joint backdrivability, impact response and quasi-direct-drive design.
Robot Data Collection
Follow robot demonstration collection through teleoperation, paired observations and actions, with real-versus-simulated data considerations for imitation learning and VLA.
Sim-to-Real
Learn how robot policies move from simulation to hardware, why model errors and delays create a reality gap, and how actuator consistency supports successful transfer.
Six-Axis Force/Torque Sensor
Explore six-axis force/torque sensing at robot wrists and ankles, its role in contact tasks, and how external measurements differ from motor-current torque estimates.
Teleoperation
Discover robot teleoperation through leader-follower arms, VR and motion tracking, and how remote task execution provides demonstrations for embodied-AI model training.
Torque Density (N·m/kg)
Calculate actuator torque per unit mass and compare rated versus peak figures, accounting for cooling, continuous load and mechanical design when selecting robot joints.
VLA Model
Understand how Vision-Language-Action models turn images and instructions into robot actions, how they differ from language models, and why demonstration data matters.
World Model
Explore how robot world models predict outcomes from states and actions, supporting planning, simulation and policy training alongside VLA and reinforcement learning.