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Form-Fitting, Large-Area Sensor Mounting for Obstacle Detection

Anna Soukhovei, Carson Kohlbrenner, Caleb Escobedo, Alexander Gholmieh, Alexander Dickhans, Alessandro Roncone

Abstract

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.

Form-Fitting, Large-Area Sensor Mounting for Obstacle Detection

Abstract

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.
Paper Structure (7 sections, 2 figures)

This paper contains 7 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Methods
  3. Procedural Skin Generation
  4. Results
  5. Hardware
  6. Printed Skin Unit
  7. Conclusion

Figures (2)

  • Figure 1: (Left) A diagram showing the procedure of digitally designing a skin unit to its deployment on a robot. A model of a sensor board and a robot model are inputted into the procedural mounting step where we use 3D graphics software to fit a skin cover around a specified link. (Right) A comparison of the point cloud representation of detected obstacles versus their position relative to the FR3 in real life. Different point colors represent depth measurements from different sensors. "Far Wave" shows a person waving their hand approximately 14 cm away from the skin unit. "Near Approach" shows a person putting their fist close to the skin unit. "Close object" shows a roll of tape situated from the sensors at close proximity. In the point cloud reconstruction of the tape roll, the hollow center of the tape is clearly defined.
  • Figure 2: (a) Photo of the skin unit. For proximity sensing, we chose to mount time of flight (ToF) imagers. Each ToF imager is attached to an index (0-7) on the multiplexer. (b) General schematic of the electrical hardware.