Fast Contact Detection Via Fusion of Joint and Inertial Sensors for Parallel Robots in Human-Robot Collaboration
Aran Mohammad, Jan Piosik, Dustin Lehmann, Thomas Seel, Moritz Schappler
AI summary
Problem
Existing proprioceptive contact detection methods suffer from phase delays due to observer error dynamics, while IMU-based acceleration estimation for serial robots requires multiple sensors. Parallel robots offer a minimal-coordinate advantage but lack investigated methods for fast, reliable contact detection using minimal sensor setups.
Approach
The method fuses data from one consumer-grade IMU mounted on the end-effector with joint encoder readings using an extended Kalman filter to directly estimate platform accelerations, which are then plugged into the robot's dynamic equations to calculate external contact forces in real time.
Key results
- Accurate platform acceleration estimation using single IMU and encoder fusion
- Contact detection within 3–39 ms via direct dynamic force calculation
- Up to 50% reduction in detection delay versus momentum observers
- Validated in simulation and real-world experiments on a planar 3-RRR parallel robot
Why it matters
This low-cost, minimal-sensor approach enables safer and more responsive human-robot collaboration without requiring complex multi-IMU setups or exteroceptive sensors.
Abstract
Fast contact detection is crucial for safe human-robot collaboration. Observers based on proprioceptive information can be used for contact detection but have first-order error dynamics, which results in delays. Sensor fusion based on inertial measure- ment units (IMUs) consisting of accelerometers and gyroscopes is advantageous for reducing delays. The acceleration estimation en- ables the direct calculation of external forces. For serial robots, the installation of multiple accelerometers and gyroscopes is required for dynamics modeling since the joint coordinates are the minimal coordinates. Alternatively, parallel robots (PRs) offer the potential to use only one IMU on the end-effector platform, which already presents the minimal coordinates of the PR. This work introduces a sensor-fusion method for contact detection using encoders and only one low-cost, consumer-grade IMU for a PR. The end-effector accelerations are estimated by an extended Kalman filter and incorporated into the dynamics to calculate external forces. In real-world experiments with a planar PR, we demonstrate that this approach reduces the detection duration by up to 50% compared to amomentumobserverandenablescollisionandclampingdetection within 3–39 ms.