5 research outputs found
Detection and Physical Interaction with Deformable Linear Objects
Deformable linear objects (e.g., cables, ropes, and threads) commonly appear
in our everyday lives. However, perception of these objects and the study of
physical interaction with them is still a growing area. There have already been
successful methods to model and track deformable linear objects. However, the
number of methods that can automatically extract the initial conditions in
non-trivial situations for these methods has been limited, and they have been
introduced to the community only recently. On the other hand, while physical
interaction with these objects has been done with ground manipulators, there
have not been any studies on physical interaction and manipulation of the
deformable linear object with aerial robots.
This workshop describes our recent work on detecting deformable linear
objects, which uses the segmentation output of the existing methods to provide
the initialization required by the tracking methods automatically. It works
with crossings and can fill the gaps and occlusions in the segmentation and
output the model desirable for physical interaction and simulation. Then we
present our work on using the method for tasks such as routing and manipulation
with the ground and aerial robots. We discuss our feasibility analysis on
extending the physical interaction with these objects to aerial manipulation
applications.Comment: Presented at ICRA 2022 2nd Workshop on Representing and Manipulating
Deformable Objects (https://deformable-workshop.github.io/icra2022/
A new dimension for magnetosensitive e-skins: active matrix integrated micro-origami sensor arrays
Magnetic sensors are widely used in our daily life for assessing the position and orientation of objects. Recently, the magnetic sensing modality has been introduced to electronic skins (e-skins), enabling remote perception of moving objects. However, the integration density of magnetic sensors is limited and the vector properties of the magnetic field cannot be fully explored since the sensors can only perceive field components in one or two dimensions. Here, we report an approach to fabricate high-density integrated active matrix magnetic sensor with three-dimensional (3D) magnetic vector field sensing capability. The 3D magnetic sensor is composed of an array of self-assembled micro-origami cubic architectures with biased anisotropic magnetoresistance (AMR) sensors manufactured in a wafer-scale process. Integrating the 3D magnetic sensors into an e-skin with embedded magnetic hairs enables real-time multidirectional tactile perception. We demonstrate a versatile approach for the fabrication of active matrix integrated 3D sensor arrays using micro-origami and pave the way for new electronic devices relying on the autonomous rearrangement of functional elements in space
Efficient Spatial Representation and Routing of Deformable One-Dimensional Objects for Manipulation
With the field of rigid-body robotics having matured in the last fifty years,
routing, planning, and manipulation of deformable objects have emerged in
recent years as a more untouched research area in many fields ranging from
surgical robotics to industrial assembly and construction. Routing approaches
for deformable objects which rely on learned implicit spatial representations
(e.g., Learning-from-Demonstration methods) make them vulnerable to changes in
the environment and the specific setup. On the other hand, algorithms that
entirely separate the spatial representation of the deformable object from the
routing and manipulation, often using a representation approach independent of
planning, result in slow planning in high dimensional space.
This paper proposes a novel approach to spatial representation combined with
route planning that allows efficient routing of deformable one-dimensional
objects (e.g., wires, cables, ropes, threads). The spatial representation is
based on the geometrical decomposition of the space into convex subspaces,
which allows an efficient coding of the configuration. Having such a
configuration, the routing problem can be solved using a dynamic programming
matching method with a quadratic time and space complexity. The proposed method
couples the routing and efficient configuration for improved planning time. Our
tests and experiments show the method correctly computing the next manipulation
action in sub-millisecond time and accomplishing various routing and
manipulation tasks.Comment: 6 page