Skip to page content
← Back to RoboticsMain menu

AVRC / Robotics

QArm

Connect robot geometry, sensing, and manipulation.

Manuals & learning linksExplore Robotics
Four arm joints · gripper · RGB-D

What the system does

QArm has four rotary arm joints in a roll–pitch–pitch–roll arrangement and a separately controlled gripper. Its joint feedback and RGB-D camera support kinematics, trajectory tracking, and visual manipulation exercises.

Inputs & outputs

Four joint commands plus a gripper command; measured joint state and camera data. Four arm DOF do not permit arbitrary independent six-DOF end-effector poses.

QArm product photograph supplied by Quanser
Product photograph and technical source: Quanser QArm ↗

Inside the experiment

ComponentRole in the system
ActuationBase, shoulder, elbow, and wrist joints; tendon-driven, two-stage gripper.
SensingJoint feedback, motor-current information, and an Intel RealSense D415 RGB-D camera. Gripper current helps assess grip strength.
InterfaceQFLEX 2 interface; host or embedded configuration depends on the workstation.
SoftwareMATLAB/Simulink, Python, and supported ROS interfaces.
Annotated QArm figure identifying arm joints, links, RGB-D camera, gripper, and interface panel
QArm components. Figure reproduced from AVRC’s laboratory equipment report. View full-size figure · Manufacturer documentation

Build understanding through evidence

Suggested AVRC learning activities. Use the linked manufacturer procedure and the instructor’s approved setup for the actual experiment.

A practical learning sequence

  1. Identify the base frame, joint limits, tool frame, and safe workspace.
  2. Compare forward-kinematics predictions with measured or observed positions.
  3. Use a supplied trajectory or pick-and-place example; document repeatability and limitations.

Teaching, outreach & research

  • Teaching: coordinate transforms, inverse kinematics, Jacobians, and vision.
  • Outreach: explain how joint motion produces a useful task.
  • Planned investigation: QArm and HD² teleoperation with supervised motion and force-feedback limits.

Go directly to the source

Official manuals and resources may have their own licensing or sign-in requirements. Use material for the exact platform generation and software release.

MATLAB, Python & QLabs setupTechnical video libraryResearch reading & examples

Prepare before operating.

Complete lab orientation and platform-specific training. Coordinate the experiment with the AVRC team in B20, Mackey Building.

Safety & access

All equipment · Faculty course integration