Hardware & control
Tactile sensing
Tactile sensing is the detection and measurement of physical contact properties at a robot's surface or contact interface. Depending on the sensor, it can report pressure or force distribution, contact location, shear, vibration, slip, texture, temperature, or deformation. Tactile data complements vision by measuring interactions that may be hidden at the point of contact.
Also known as: robot tactile sensing, robotic tactile sensing
Updated
Contact produces information that cameras can miss
Dahiya and colleagues define tactile sensing around detecting and measuring contact parameters over a specified area, with sensor-level processing before higher-level interpretation. Robot implementations range from single contact switches to fingertip arrays, optical tactile sensors and large-area electronic skin.
Vision may show that fingers surround an object while hiding whether the object is slipping or how pressure is distributed. Tactile sensing can reveal contact onset, local force changes, vibration or deformation during grasping, insertion, wiping and other contact-rich tasks.
Tactile, force-torque and proprioceptive signals differ
A tactile array measures contact locally at or near a surface and may preserve spatial structure. A wrist force–torque sensor measures the resultant forces and moments transmitted through the wrist, but usually cannot identify the complete pressure pattern across several fingertips. Motor currents and joint torque estimates are internal signals that can imply contact without measuring the interface directly.
Proprioception describes the robot's own configuration and motion, such as joint position and velocity. Tactile sensing is generally exteroceptive because it reports interaction at the boundary between body and environment. A manipulation system can combine all of these streams.
Tactile data needs calibration and timing
Raw values are difficult to compare without sensor type, location, units, range, resolution, sampling rate, calibration and drift information. A dataset should also align tactile samples with camera frames, hand pose, actions and outcomes.
Contact sensors can saturate, wear, detach or respond differently after remounting. Training records should preserve those limitations and any filtering or normalisation. A tactile channel adds value when its physical meaning and relationship to the task remain recoverable.
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Related terms
Hardware & control
Proprioception
Proprioception is sensing of a robot’s own internal configuration and motion rather than the external scene. For a humanoid it commonly includes joint positions and velocities, actuator effort or torque, and inertial measurements of body rotation and acceleration. These signals support state estimation and feedback control but do not, by themselves, directly describe nearby objects or terrain.
Hardware & control
Force–torque sensing
Force–torque sensing is the measurement of forces and rotational moments transmitted through a robot interface, commonly with a six-axis sensor reporting three force components and three torque components. The combined quantity is a wrench expressed at a specified origin and in a specified coordinate frame. It measures the resultant load at the sensor, not a spatial pressure map across every contact.
Hardware & control
Gripper
A gripper is a robot end effector designed to seize and hold an object. It may use fingers, jaws, suction, magnetism, adhesion, or another grasping mechanism. A gripper can open and close with one command or expose several independently controlled joints, but it is not synonymous with every end effector or with a complete robot hand.
Hardware & control
Robot manipulation
Robot manipulation is a robot's controlled physical interaction with objects or its environment to change or maintain their state. It includes grasping, carrying, pushing, pulling, inserting, wiping, folding, tool use, and other tasks performed through selective contact. Manipulation can use a gripper, hand, tool, arm, or another part of the robot.
Hardware & control
Impedance control
Impedance control regulates the dynamic relationship between a robot’s motion error and the force or torque it exerts, usually by giving the robot virtual stiffness, damping and sometimes inertia. It lets an end effector or limb yield predictably during contact instead of trying to hold an exact position regardless of interaction forces.
Data & collection
Robot training data
Robot training data is recorded experience used to train, fine-tune, or adapt models for robot perception, prediction, planning, or control. It can include sensor observations, robot state, actions, task instructions, rewards or outcomes, demonstrations, failures, and embodiment metadata. Not every dataset contains every field, but their timing and physical meaning must be clear.