Definition
A force-torque (F/T) sensor measures the three linear forces (Fx, Fy, Fz) and three torques (Tx, Ty, Tz) acting on it, providing a complete 6-axis picture of the contact wrench. Mounted at the robot's wrist (between the last joint and the end-effector), an F/T sensor tells the controller exactly how much force the gripper is exerting on an object and in which direction.
This information is critical for tasks where vision alone is insufficient: inserting a peg into a tight hole requires sensing contact forces to avoid jamming; polishing a surface requires maintaining consistent normal force; and assembly operations require detecting when parts are seated correctly. Without force sensing, robots must rely on position control alone, which leads to either excessive force (damaging parts) or insufficient contact (dropping parts).
In the context of robot learning, F/T data provides an additional observation modality alongside camera images and joint positions. Policies trained with force observations can learn contact-rich behaviors — such as wiping, screwing, and inserting — that are extremely difficult to learn from vision alone. During teleoperation for data collection, recording F/T data alongside visual observations creates richer training datasets for imitation learning.
How F/T Sensors Work
The two dominant sensing technologies are strain gauges and capacitive elements. Strain-gauge sensors use a precisely machined metal body (typically a cruciform or Stewart platform geometry) instrumented with bonded strain gauges. When external forces are applied, the body deforms microscopically, changing the resistance of the strain gauges. A Wheatstone bridge circuit converts these resistance changes into voltage signals proportional to the applied force and torque.
Capacitive sensors use arrays of capacitor plates separated by a compressible dielectric. Applied forces change the gap between plates, altering capacitance. These sensors can be made smaller and lighter than strain-gauge designs, making them suitable for fingertip sensing on dexterous hands.
Both types output analog signals that are digitized by an onboard ADC and transmitted to the robot controller via EtherCAT, USB, or Ethernet at 1–8 kHz. The raw signal is typically filtered (low-pass, 50–500 Hz cutoff) to remove vibration noise. Gravity compensation — subtracting the weight of the end-effector and any held object — is applied in software to isolate contact forces from gravitational loads.
Top Sensors
- ATI Industrial Automation (Gamma, Mini45, Nano17) — The industry standard for research and industrial robotics. Strain-gauge based, extremely accurate (0.1% full-scale), wide range of models from fingertip-sized (Nano17: 12 mm diameter) to heavy-duty (Omega: 6000 N range). Price: $3K–$15K.
- Robotiq FT300 — Designed for collaborative robots (UR, Fanuc). Built-in ROS driver, easy mounting on UR e-series. Range: 300 N force, 30 Nm torque. Competitive price (~$3K) and good for most research manipulation tasks.
- OnRobot HEX-E/H — 6-axis sensor integrated with OnRobot's tool changer ecosystem. Automatic tool recognition and gravity compensation. Designed for quick industrial deployment rather than research flexibility.
- XELA uSkin / BioTac — Tactile sensing arrays that provide distributed force measurements across a surface, rather than a single 6-axis wrench. Used on dexterous hands and fingertips. Enable slip detection and texture recognition.
Integration with Robot Control
Admittance control: The F/T sensor measures external forces, and the controller adjusts the position trajectory to accommodate them. The robot moves as if connected to the environment through a virtual spring-damper. This is the most common integration pattern for position-controlled robots (UR, Fanuc, ABB).
Impedance control: The controller directly regulates the relationship between motion and force using the F/T signal. The robot behaves like a programmable mass-spring-damper system. This requires torque-controlled actuators (Franka Panda, KUKA iiwa) and provides more responsive compliance than admittance control.
ROS2 integration: Most F/T sensors publish to the geometry_msgs/WrenchStamped topic. ROS2 control frameworks (ros2_control, MoveIt Servo) can consume this data for force-limited trajectories, contact detection, and hybrid force-position control. The force_torque_sensor_broadcaster package provides a standard interface.
Key Specifications
Range: Maximum measurable force and torque before saturation. Must exceed the expected task forces with margin. Typical ranges: 50–500 N for manipulation research, 1000–6000 N for industrial applications.
Resolution: Smallest detectable force change. ATI Nano17 achieves 1/160 N resolution. Higher resolution enables detection of subtle contact events like surface texture changes or incipient slip.
Overload protection: How much force the sensor can withstand without damage (typically 5–20x the rated range). Critical for research settings where crashes happen. Some sensors include mechanical stops to prevent overload.
Sample rate: Output frequency. 1 kHz is sufficient for most manipulation. High-speed assembly or impact detection may require 4–8 kHz.
Key Papers
- Hogan, N. (1985). "Impedance Control: An Approach to Manipulation." ASME Journal of Dynamic Systems. The foundational paper on using force sensing for compliant robot control, introducing the impedance control framework.
- Luo, J. et al. (2024). "Multi-Modal Imitation Learning with Force Observations." CoRL 2024. Demonstrated that adding F/T observations to visual imitation learning significantly improves success on contact-rich manipulation tasks.
- Lee, M. A. et al. (2019). "Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks." ICRA 2019. Showed how to combine vision and tactile/force signals for robust manipulation policies.
Related Terms
- Impedance Control — Control strategy that uses F/T feedback for compliant behavior
- End-Effector — The device where F/T sensors are typically mounted
- Teleoperation — F/T data enables haptic feedback and force recording during data collection
- Grasp Planning — Force analysis determines grasp stability
- Policy Learning — F/T observations as input to force-aware manipulation policies
Add Force Sensing to Your Robot
Silicon Valley Robotics Center provides F/T sensor integration services for common research and industrial robots. We can help you select the right sensor, mount and calibrate it, configure ROS2 drivers, and set up impedance or admittance control for your contact-rich manipulation tasks.