3 research outputs found
Human keypoint detection for close proximity human-robot interaction
We study the performance of state-of-the-art human keypoint detectors in the
context of close proximity human-robot interaction. The detection in this
scenario is specific in that only a subset of body parts such as hands and
torso are in the field of view. In particular, (i) we survey existing datasets
with human pose annotation from the perspective of close proximity images and
prepare and make publicly available a new Human in Close Proximity (HiCP)
dataset; (ii) we quantitatively and qualitatively compare state-of-the-art
human whole-body 2D keypoint detection methods (OpenPose, MMPose, AlphaPose,
Detectron2) on this dataset; (iii) since accurate detection of hands and
fingers is critical in applications with handovers, we evaluate the performance
of the MediaPipe hand detector; (iv) we deploy the algorithms on a humanoid
robot with an RGB-D camera on its head and evaluate the performance in 3D human
keypoint detection. A motion capture system is used as reference.
The best performing whole-body keypoint detectors in close proximity were
MMPose and AlphaPose, but both had difficulty with finger detection. Thus, we
propose a combination of MMPose or AlphaPose for the body and MediaPipe for the
hands in a single framework providing the most accurate and robust detection.
We also analyse the failure modes of individual detectors -- for example, to
what extent the absence of the head of the person in the image degrades
performance. Finally, we demonstrate the framework in a scenario where a
humanoid robot interacting with a person uses the detected 3D keypoints for
whole-body avoidance maneuvers.Comment: 8 pages 8 figure
Effect of Active and Passive Protective Soft Skins on Collision Forces in Human-robot Collaboration
Soft electronic skins are one of the means to turn an industrial manipulator
into a collaborative robot. For manipulators that are already fit for physical
human-robot collaboration, soft skins can make them safer. In this work, we
study the after impact behavior of two collaborative manipulators (UR10e and
KUKA LBR iiwa) and one classical industrial manipulator (KUKA Cybertech), in
presence or absence of an industrial protective skin (AIRSKIN). In addition, we
isolate the effects of the passive padding and the active contribution of the
sensor to robot reaction. We present a total of 2250 collision measurements and
study the impact force, contact duration, clamping force, and impulse. The
dataset is publicly available. We summarize our results as follows. For
transient collisions, the passive skin properties lowered the impact forces by
about 40 %. During quasi-static contact, the effect of skin covers -- active or
passive -- cannot be isolated from the collision detection and reaction by the
collaborative robots. Important effects of the stop categories triggered by the
active protective skin were found. We systematically compare the different
settings and the empirically established safe velocities with prescriptions by
the ISO/TS 15066. In some cases, up to the quadruple of the ISO/TS 15066
prescribed velocity can comply with the impact force limits and thus be
considered safe. We propose an extension of the formulas relating impact force
and permissible velocity that take into account the stiffness and compressible
thickness of the protective cover, leading to better predictions of the
collision forces. At the same time, this work emphasizes the need for in situ
measurements as all the factors we studied -- presence of active/passive skin,
safety stop settings, robot collision reaction, impact direction, and, of
course, velocity -- have effects on the force evolution after impact.Comment: 18 pages, 15 figure