72 research outputs found
Linear Time-Varying MPC for Nonprehensile Object Manipulation with a Nonholonomic Mobile Robot
This paper proposes a technique to manipulate an object with a nonholonomic
mobile robot by pushing, which is a nonprehensile manipulation motion
primitive. Such a primitive involves unilateral constraints associated with the
friction between the robot and the manipulated object. Violating this
constraint produces the slippage of the object during the manipulation,
preventing the correct achievement of the task. A linear time-varying model
predictive control is designed to include the unilateral constraint within the
control action properly. The approach is verified in a dynamic simulation
environment through a Pioneer 3-DX wheeled robot executing the pushing
manipulation of a package
Human-Multirobot Collaborative Mobile Manipulation: the Omnid Mocobots
The Omnid human-collaborative mobile manipulators are an experimental
platform for testing control architectures for autonomous and
human-collaborative multirobot mobile manipulation. An Omnid consists of a
mecanum-wheel omnidirectional mobile base and a series-elastic Delta-type
parallel manipulator, and it is a specific implementation of a broader class of
mobile collaborative robots ("mocobots") suitable for safe human
co-manipulation of delicate, flexible, and articulated payloads. Key features
of mocobots include passive compliance, for the safety of the human and the
payload, and high-fidelity end-effector force control independent of the
potentially imprecise motions of the mobile base. We describe general
considerations for the design of teams of mocobots; the design of the Omnids in
light of these considerations; manipulator and mobile base controllers to
achieve useful multirobot collaborative behaviors; and initial experiments in
human-multirobot collaborative mobile manipulation of large, unwieldy payloads.
For these experiments, the only communication among the humans and Omnids is
mechanical, through the payload.Comment: 8 pages, 10 figures. Videos available at
https://www.youtube.com/watch?v=SEuFfONryL0. Submitted to IEEE Robotics and
Automation Letters (RA-L
Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
In this work, we consider a group of robots working together to manipulate a
rigid object to track a desired trajectory in . The robots do not know
the mass or friction properties of the object, or where they are attached to
the object. They can, however, access a common state measurement, either from
one robot broadcasting its measurements to the team, or by all robots
communicating and averaging their state measurements to estimate the state of
their centroid. To solve this problem, we propose a decentralized adaptive
control scheme wherein each agent maintains and adapts its own estimate of the
object parameters in order to track a reference trajectory. We present an
analysis of the controller's behavior, and show that all closed-loop signals
remain bounded, and that the system trajectory will almost always (except for
initial conditions on a set of measure zero) converge to the desired
trajectory. We study the proposed controller's performance using numerical
simulations of a manipulation task in 3D, as well as hardware experiments which
demonstrate our algorithm on a planar manipulation task. These studies, taken
together, demonstrate the effectiveness of the proposed controller even in the
presence of numerous unmodeled effects, such as discretization errors and
complex frictional interactions
Force-based Pose Regulation of a Cable-Suspended Load Using UAVs with Force Bias
International audienceThis work studies how force measurement/estimation biases affect the force-based cooperative manipulation of a beam-like load suspended with cables by two aerial robots. Indeed, force biases are especially relevant in a force-based manipulation scenario in which direct communication is not relied upon. First, we compute the equilibrium configurations of the system. Then, we show that inducing an internal force in the load augments the robustness of the load attitude error and its sensitivity to force-bias variations. Eventually, we propose a method for zeroing the load position error. The results are validated through numerical simulations and experiments
Multi-Robot Object Transport Motion Planning with a Deformable Sheet
Using a deformable sheet to handle objects is convenient and found in many
practical applications. For object manipulation through a deformable sheet that
is held by multiple mobile robots, it is a challenging task to model the
object-sheet interactions. We present a computational model and algorithm to
capture the object position on the deformable sheet with changing robotic team
formations. A virtual variable cables model (VVCM) is proposed to simplify the
modeling of the robot-sheet-object system. With the VVCM, we further present a
motion planner for the robotic team to transport the object in a
three-dimensional (3D) cluttered environment. Simulation and experimental
results with different robot team sizes show the effectiveness and versatility
of the proposed VVCM. We also compare and demonstrate the planning results to
avoid the obstacle in 3D space with the other benchmark planner.Comment: 8 pages, 10 figures, accepted by RAL&CASE 2022 in June 24, 202
Equilibria, Stability, and Sensitivity for the Aerial Suspended Beam Robotic System subject to Parameter Uncertainty
This work studies how parametric uncertainties affect the cooperative
manipulation of a cable-suspended beam-shaped load by means of two aerial
robots not explicitly communicating with each other. In particular, the work
sheds light on the impact of the uncertain knowledge of the model parameters
available to an established communication-less force-based controller. First,
we find the closed-loop equilibrium configurations in the presence of the
aforementioned uncertainties, and then we study their stability. Hence, we show
the fundamental role played in the robustness of the load attitude control by
the internal force induced in the manipulated object by non-vertical cables.
Furthermore, we formally study the sensitivity of the attitude error to such
parametric variations, and we provide a method to act on the load position
error in the presence of the uncertainties. Eventually, we validate the results
through an extensive set of numerical tests in a realistic simulation
environment including underactuated aerial vehicles and sagging-prone cables,
and through hardware experiments
Modeling And Control For Robotic Assistants: Single And Multi-Robot Manipulation
As advances are made in robotic hardware, the complexity of tasks they are capable of performing also increases. One goal of modern robotics is to introduce robotic platforms that require very little augmentation of their environments to be effective and robust. Therefore the challenge for a roboticist is to develop algorithms and control strategies that leverage knowledge of the task while retaining the ability to be adaptive, adjusting to perturbations in the environment and task assumptions. This work considers approaches to these challenges in the context of a wet-lab robotic assistant. The tasks considered are cooperative transport with limited communication between team members, and robot-assisted rapid experiment preparation requiring pouring reagents from open containers useful for research and development scientists. For cooperative transport, robots must be able to plan collision-free trajectories and agree on a final destination to minimize internal forces on the carried load. Robot teammates are considered, where robots must reach consensus to minimize internal forces. The case of a human leader, and robot follower is then considered, where robots must use non-verbal information to estimate the human leader\u27s intended pose for the carried load. For experiment preparation, the robot must pour precisely from open containers with known fluid in a single attempt. Two scenarios examined are when the geometries of the pouring and receiving containers and behaviors are known, and when the pourer must be approximated. An analytical solution is presented for a given geometry in the first instance. In the second instance, a combination of online system identification and leveraging of model priors is used to achieve the precision-pour in a single attempt with considerations for long-term robot deployment. The main contributions of this work are considerations and implementations for making robots capable of performing complex tasks with an emphasis on combining model-based and data-driven approaches for best performance
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