Form-Fitting, Large-Area Sensor Mounting for Obstacle Detection
This addresses the challenge of sensor placement for obstacle detection in robotics, offering a practical solution for robot skin applications, though it appears incremental as it builds on existing CAD and sensor mounting techniques.
The paper tackles the problem of mounting sensors on robot links for large-area obstacle detection by introducing a low-cost, procedurally generated skin unit that fits nondevelopable surfaces without requiring pre-calibration, and demonstrates it by constructing point cloud images of obstacles using an array of ToF imagers on a Franka Research 3 robot arm.
We introduce a low-cost method for mounting sensors onto robot links for large-area sensing coverage that does not require the sensor's positions or orientations to be calibrated before use. Using computer aided design (CAD), a robot skin covering, or skin unit, can be procedurally generated to fit around a nondevelopable surface, a 3D surface that cannot be flattened into a 2D plane without distortion, of a robot. The skin unit embeds mounts for printed circuit boards of any size to keep sensors in fixed and known locations. We demonstrate our method by constructing point cloud images of obstacles within the proximity of a Franka Research 3 robot's operational environment using an array of time of flight (ToF) imagers mounted on a printed skin unit and attached to the robot arm.