7,986 research outputs found
A flexible sensor technology for the distributed measurement of interaction pressure
We present a sensor technology for the measure of the physical human-robot interaction pressure developed in the last years at Scuola Superiore Sant'Anna. The system is composed of flexible matrices of opto-electronic sensors covered by a soft silicone cover. This sensory system is completely modular and scalable, allowing one to cover areas of any sizes and shapes, and to measure different pressure ranges. In this work we present the main application areas for this technology. A first generation of the system was used to monitor human-robot interaction in upper- (NEUROExos; Scuola Superiore Sant'Anna) and lower-limb (LOPES; University of Twente) exoskeletons for rehabilitation. A second generation, with increased resolution and wireless connection, was used to develop a pressure-sensitive foot insole and an improved human-robot interaction measurement systems. The experimental characterization of the latter system along with its validation on three healthy subjects is presented here for the first time. A perspective on future uses and development of the technology is finally drafted
Robot Excitation Trajectories for Dynamic Parameter Estimation using Optimized B-Splines
In this paper we adressed the problem of finding
exciting trajectories for the identification of manipulator link
inertia parameters. This can be formulated as a constraint
nonlinear optimization problem. The new approach in the
presented method is the parameterization of the trajectories
with optimized B-splines. Experiments are carried out on a
7 joint Light-Weight robot with torque sensoring in each
joint. Thus, unmodeled joint friction and noisy motor current
measurements must not be taken into account. The estimated
dynamic model is verified on a different validation trajectory.
The results show a clear improvement of the estimated dynamic
model compared to a CAD-valued model
Benchmarking Cerebellar Control
Cerebellar models have long been advocated as viable models
for robot dynamics control. Building on an increasing insight
in and knowledge of the biological cerebellum, many models have been
greatly refined, of which some computational models have emerged
with useful properties with respect to robot dynamics control.
Looking at the application side, however, there is a totally different
picture. Not only is there not one robot on the market which uses
anything remotely connected with cerebellar control, but even in
research labs most testbeds for cerebellar models are restricted to
toy problems. Such applications hardly ever exceed the complexity of
a 2 DoF simulated robot arm; a task which is hardly representative for
the field of robotics, or relates to realistic applications.
In order to bring the amalgamation of the two fields forwards, we
advocate the use of a set of robotics benchmarks, on which existing
and new computational cerebellar models can be comparatively tested.
It is clear that the traditional approach to solve robotics dynamics
loses ground with the advancing complexity of robotic structures;
there is a desire for adaptive methods which can compete as traditional
control methods do for traditional robots.
In this paper we try to lay down the successes and problems in the
fields of cerebellar modelling as well as robot dynamics control.
By analyzing the common ground, a set of benchmarks is suggested
which may serve as typical robot applications for cerebellar models
Collision Detection and Reaction: A Contribution to Safe Physical Human-Robot Interaction
In the framework of physical Human-Robot Interaction
(pHRI), methodologies and experimental tests are
presented for the problem of detecting and reacting to collisions
between a robot manipulator and a human being. Using a
lightweight robot that was especially designed for interactive
and cooperative tasks, we show how reactive control strategies
can significantly contribute to ensuring safety to the human
during physical interaction. Several collision tests were carried
out, illustrating the feasibility and effectiveness of the proposed
approach. While a subjective “safety” feeling is experienced by
users when being able to naturally stop the robot in autonomous
motion, a quantitative analysis of different reaction strategies
was lacking. In order to compare these strategies on an objective
basis, a mechanical verification platform has been built. The
proposed collision detection and reactions methods prove to
work very reliably and are effective in reducing contact forces
far below any level which is dangerous to humans. Evaluations
of impacts between robot and human arm or chest up to a
maximum robot velocity of 2.7 m/s are presented
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