4,129 research outputs found
Quadrotor Manipulation System: Development of a Robust Contact Force Estimation and Impedance Control Scheme Based on DOb and FTRLS
The research on aerial manipulation systems has been increased rapidly in
recent years. These systems are very attractive for a wide range of
applications due to their unique features. However, dynamics, control and
manipulation tasks of such systems are quite challenging because they are
naturally unstable, have very fast dynamics, have strong nonlinearities, are
very susceptible to parameters variations due to carrying a payload besides the
external disturbances, and have complex inverse kinematics. In addition, the
manipulation tasks require estimating (applying) a certain force of (at) the
end-effector as well as the accurate positioning of it. Thus, in this article,
a robust force estimation and impedance control scheme is proposed to address
these issues. The robustness is achieved based on the Disturbance Observer
(DOb) technique. Then, a tracking and performance low computational linear
controller is used. For teleoperation purpose, the contact force needs to be
identified. However, the current developed techniques for force estimation have
limitations because they are based on ignoring some dynamics and/or requiring
of an indicator of the environment contact. Unlike these techniques, we propose
a technique based on linearization capabilities of DOb and a Fast Tracking
Recursive Least Squares (FTRLS) algorithm. The complex inverse kinematics
problem of such a system is solved by a Jacobin based algorithm. The stability
analysis of the proposed scheme is presented. The algorithm is tested to
achieve tracking of task space reference trajectories besides the impedance
control. The efficiency of the proposed technique is enlightened via numerical
simulation
Compare Contact Model-based Control and Contact Model-free Learning: A Survey of Robotic Peg-in-hole Assembly Strategies
In this paper, we present an overview of robotic peg-in-hole assembly and
analyze two main strategies: contact model-based and contact model-free
strategies. More specifically, we first introduce the contact model control
approaches, including contact state recognition and compliant control two
steps. Additionally, we focus on a comprehensive analysis of the whole robotic
assembly system. Second, without the contact state recognition process, we
decompose the contact model-free learning algorithms into two main subfields:
learning from demonstrations and learning from environments (mainly based on
reinforcement learning). For each subfield, we survey the landmark studies and
ongoing research to compare the different categories. We hope to strengthen the
relation between these two research communities by revealing the underlying
links. Ultimately, the remaining challenges and open questions in the field of
robotic peg-in-hole assembly community is discussed. The promising directions
and potential future work are also considered
Simultaneously encoding movement and sEMG-based stiffness for robotic skill learning
Transferring human stiffness regulation strategies to robots enables them to effectively and efficiently acquire adaptive impedance control policies to deal with uncertainties during the accomplishment of physical contact tasks in an unstructured environment. In this work, we develop such a physical human-robot interaction (pHRI) system which allows robots to learn variable impedance skills from human demonstrations. Specifically, the biological signals, i.e., surface electromyography (sEMG) are utilized for the extraction of human arm stiffness features during the task demonstration. The estimated human arm stiffness is then mapped into a robot impedance controller. The dynamics of both movement and stiffness are simultaneously modeled by using a model combining the hidden semi-Markov model (HSMM) and the Gaussian mixture regression (GMR). More importantly, the correlation between the movement information and the stiffness information is encoded in a systematic manner. This approach enables capturing uncertainties over time and space and allows the robot to satisfy both position and stiffness requirements in a task with modulation of the impedance controller. The experimental study validated the proposed approach
An Omnidirectional Aerial Manipulation Platform for Contact-Based Inspection
This paper presents an omnidirectional aerial manipulation platform for
robust and responsive interaction with unstructured environments, toward the
goal of contact-based inspection. The fully actuated tilt-rotor aerial system
is equipped with a rigidly mounted end-effector, and is able to exert a 6
degree of freedom force and torque, decoupling the system's translational and
rotational dynamics, and enabling precise interaction with the environment
while maintaining stability. An impedance controller with selective apparent
inertia is formulated to permit compliance in certain degrees of freedom while
achieving precise trajectory tracking and disturbance rejection in others.
Experiments demonstrate disturbance rejection, push-and-slide interaction, and
on-board state estimation with depth servoing to interact with local surfaces.
The system is also validated as a tool for contact-based non-destructive
testing of concrete infrastructure.Comment: Accepted submission to Robotics: Science and Systems conference 2019.
9 pages, 12 figure
A Framework for Fine Robotic Assembly
Fine robotic assembly, in which the parts to be assembled are small and
fragile and lie in an unstructured environment, is still out of reach of
today's industrial robots. The main difficulties arise in the precise
localization of the parts in an unstructured environment and the control of
contact interactions. Our contribution in this paper is twofold. First, we
propose a taxonomy of the manipulation primitives that are specifically
involved in fine assembly. Such a taxonomy is crucial for designing a scalable
robotic system (both hardware and software) given the complexity of real-world
assembly tasks. Second, we present a hardware and software architecture where
we have addressed, in an integrated way, a number of issues arising in fine
assembly, such as workspace optimization, external wrench compensation,
position-based force control, etc. Finally, we show the above taxonomy and
architecture in action on a highly dexterous task -- bimanual pin insertion --
which is one of the key steps in our long term project, the autonomous assembly
of an IKEA chair.Comment: 8 pages, 7 figures, 2 table
Development of an Autonomous Sanding Robot with Structured-Light Technology
Large demand for robotics and automation has been reflected in the sanding
works, as current manual operations are labor-intensive, without consistent
quality, and also subject to safety and health issues. While several machines
have been developed to automate one or two steps in the sanding works, the
autonomous capability of existing solutions is relatively low, and the human
assistance or supervision is still heavily required in the calibration of
target objects or the planning of robot motion and tasks. This paper presents
the development of an autonomous sanding robot, which is able to perform the
sanding works on an unknown object automatically, without any prior calibration
or human intervention. The developed robot works as follows. First, the target
object is scanned then modeled with the structured-light camera. Second, the
robot motion is planned to cover all the surfaces of the object with an
optimized transition sequence. Third, the robot is controlled to perform the
sanding on the object under the desired impedance model. A prototype of the
sanding robot is fabricated and its performance is validated in the task of
sanding a batch of wooden boxes. With sufficient degrees of freedom (DOFs) and
the module design for the end effector, the developed robot is able to provide
a general solution to the autonomous sanding on many other different objects.Comment: 7 pages, 11 figures, IEEE/RSJ International Conference on Intelligent
Robots and Systems 201
Segmenting and Sequencing of Compliant Motions
This paper proposes an approach for segmenting a task consisting of compliant
motions into phases, learning a primitive for each segmented phase of the task,
and reproducing the task by sequencing primitives online based on the learned
model. As compliant motions can "probe" the environment, using the interaction
between the robot and the environment to detect phase transitions can make the
transitions less prone to positional errors. This intuition leads us to model a
task with a non-homogeneous Hidden Markov Model (HMM), wherein hidden phase
transition probabilities depend on the interaction with the environment (wrench
measured by an F/T sensor). Expectation-maximization algorithm is employed in
estimating the parameters of the HMM model. During reproduction, the phase
changes of a task are detected online using the forward algorithm, with the
parameters learned from demonstrations. Cartesian impedance controller
parameters are learned from the demonstrations to reproduce each phase of the
task. The proposed approach is studied with a KUKA LWR4+ arm in two setups.
Experiments show that the method can successfully segment and reproduce a task
consisting of compliant motions with one or more demonstrations, even when
demonstrations do not have the same starting position and external forces occur
from different directions. Finally, we demonstrate that the method can also
handle rotational motions
Fully distributed cooperation for networked uncertain mobile manipulators
This paper investigates a fully distributed cooperation scheme for networked
mobile manipulators. To achieve cooperative task allocation in a distributed
way, an adaptation-based estimation law is established for each robotic agent
to estimate the desired local trajectory. In addition, wrench synthesis is
analyzed in detail to lay a solid foundation for tight cooperation tasks.
Together with the estimated task, a set of distributed adaptive controllers is
proposed to achieve motion synchronization of the mobile manipulator ensemble
over a directed graph with a spanning tree irrespective of the kinematic and
dynamic uncertainties in both the mobile manipulators and the tightly grasped
object. The controlled synchronization alleviates the performance degradation
caused by the estimation/tracking discrepancy during the transient phase. The
proposed scheme requires no persistent excitation condition and avoids the use
of noisy Cartesian-space velocities. Furthermore, it is independent from the
object's center of mass by employing formation-based task allocation and a
task-oriented strategy. These attractive attributes facilitate the practical
application of the scheme. It is theoretically proven that convergence of the
cooperative task tracking error is guaranteed. Simulation results validate the
efficacy and demonstrate the expected performance of the proposed scheme.Comment: 18 pages with 13 figures. Final version with experiment to appear in
IEEE Transactions on Robotic
Human interaction dynamics for its use in mobile robotics: Impedance control for leader-follower formation
A complete characterization of the behavior in human-robot interactions (HRI) includes both: the behavioral dynamics and the control laws that characterize how the behavior is regulated with the perception data. In this way, this work proposes a leader-follower coordinate control based on an impedance control that allows to establish a dynamic relation between social forces and motion error. For this, a scheme is presented to identify the impedance based on fictitious social forces, which are described by distance-based potential fields. As part of the validation procedure, we present an experimental comparison to select the better of two different fictitious force structures. The criteria are determined by two qualities: least impedance errors during the validation procedure and least parameter variance during the recursive estimation procedure. Finally, with the best fictitious force and its identified impedance, an impedance control is designed for a mobile robot Pioneer 3AT, which is programmed to follow a human in a structured scenario. According to results, and under the hypothesis that moving like humans will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction.Fil: Herrera Anda, Daniel Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Roberti, Flavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Toibero, Juan Marcos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Carelli Albarracin, Ricardo Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin
Control of an Aerial Manipulator using On-line Parameter Estimator for an Unknown Payload
This paper presents an estimation and control algorithm for an aerial
manipulator using a hexacopter with a 2-DOF robotic arm. The unknown parameters
of a payload are estimated by an on-line estimator based on parametrization of
the aerial manipulator dynamics. With the estimated mass information and the
augmented passivity-based controller, the aerial manipulator can fly with the
unknown object. Simulation for an aerial manipulator is performed to compare
estimation performance between the proposed control algorithm and conventional
adaptive sliding mode controller. Experimental results show a successful flight
of a custom-made aerial manipulator while the unknown parameters related to an
additional payload were estimated satisfactorily.Comment: 2015 IEEE International Conference on Automation Science and
Engineerin
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