1,233 research outputs found
Whole-Body MPC for a Dynamically Stable Mobile Manipulator
Autonomous mobile manipulation offers a dual advantage of mobility provided
by a mobile platform and dexterity afforded by the manipulator. In this paper,
we present a whole-body optimal control framework to jointly solve the problems
of manipulation, balancing and interaction as one optimization problem for an
inherently unstable robot. The optimization is performed using a Model
Predictive Control (MPC) approach; the optimal control problem is transcribed
at the end-effector space, treating the position and orientation tasks in the
MPC planner, and skillfully planning for end-effector contact forces. The
proposed formulation evaluates how the control decisions aimed at end-effector
tracking and environment interaction will affect the balance of the system in
the future. We showcase the advantages of the proposed MPC approach on the
example of a ball-balancing robot with a robotic manipulator and validate our
controller in hardware experiments for tasks such as end-effector pose tracking
and door opening
Towards retrieving force feedback in robotic-assisted surgery: a supervised neuro-recurrent-vision approach
Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One of them is the lack of force feedback which restricts the surgeon's sense of touch and might reduce precision during a procedure. To overcome this limitation, we propose a novel force estimation approach that combines a vision based solution with supervised learning to estimate the applied force and provide the surgeon with a suitable representation of it. The proposed solution starts with extracting the geometry of motion of the heart's surface by minimizing an energy functional to recover its 3D deformable structure. A deep network, based on a LSTM-RNN architecture, is then used to learn the relationship between the extracted visual-geometric information and the applied force, and to find accurate mapping between the two. Our proposed force estimation solution avoids the drawbacks usually associated with force sensing devices, such as biocompatibility and integration issues. We evaluate our approach on phantom and realistic tissues in which we report an average root-mean square error of 0.02 N.Peer ReviewedPostprint (author's final draft
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
Proprioceptive Robot Collision Detection through Gaussian Process Regression
This paper proposes a proprioceptive collision detection algorithm based on
Gaussian Regression. Compared to sensor-based collision detection and other
proprioceptive algorithms, the proposed approach has minimal sensing
requirements, since only the currents and the joint configurations are needed.
The algorithm extends the standard Gaussian Process models adopted in learning
the robot inverse dynamics, using a more rich set of input locations and an
ad-hoc kernel structure to model the complex and non-linear behaviors due to
frictions in quasi-static configurations. Tests performed on a Universal Robots
UR10 show the effectiveness of the proposed algorithm to detect when a
collision has occurred.Comment: Published at ACC 201
Modeling, Stability Analysis, and Testing of a Hybrid Docking Simulator
A hybrid docking simulator is a hardware-in-the-loop (HIL) simulator that
includes a hardware element within a numerical simulation loop. One of the
goals of performing a HIL simulation at the European Proximity Operation
Simulator (EPOS) is the verification and validation of the docking phase in an
on-orbit servicing mission.....Comment: 30 papge
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