Vibration Free Flexible Object Handling with a Robot Manipulator Using Learning Control

Many industries extensively use flexible materials. Effective approaches for handling flexible objects with a robot manipulator must address residual vibrations. Existing solutions rely on complex models, use additional instrumentation for sensing the vibrations, or do not exploit the repetitive nature of most industrial tasks. This paper develops an iterative learning control approach that jointly learns model parameters and residual dynamics using only the interoceptive sensors of the robot. The learned model is subsequently utilized to design optimal (PTP) trajectories that accounts for residual vibration, nonlinear kinematics of the manipulator and joint limits. We experimentally show that the proposed approach reduces the residual vibrations by an order of magnitude compared with optimal vibration suppression using the analytical model and threefold compared with the available state-of-the-art method. These results demonstrate that effective handling of a flexible object does not require neither complex models nor additional instrumentation.Comment: Have been submitted to IFAC World Congres

Optimal input design for flat systems using B-splines

This paper deals with optimal design of input signals for linear, controllable systems, by means of their flat output. The flat output is parametrized by a polynomial spline and a linear problem is formulated in which both the spline coefficients and the knot locations are found simultaneously. Conservative constraints on the spline coefficients ensure that semi-infinite bounds are never violated and numerical results show that the amount of conservatism is little.status: publishe

Evaluation of MPC-based Imitation Learning for Human-like Autonomous Driving

This work evaluates and analyzes the combination of imitation learning (IL) and differentiable model predictive control (MPC) for the application of human-like autonomous driving. We combine MPC with a hierarchical learning-based policy, and measure its performance in open-loop and closed-loop with metrics related to safety, comfort and similarity to human driving characteristics. We also demonstrate the value of augmenting open-loop behavioral cloning with closed-loop training for a more robust learning, approximating the policy gradient through time with the state space model used by the MPC. We perform experimental evaluations on a lane keeping control system, learned from demonstrations collected on a fixed-base driving simulator, and show that our imitative policies approach the human driving style preferences.Comment: This work has been submitted to IFAC for possible publication. arXiv admin note: text overlap with arXiv:2206.1234

Town of Lamoine Maine 2001 Annual Report

status: publishe

Experimental study on active structural acoustic control of rotating machinery using rotating piezo-based inertial actuators

info:eu-repo/semantics/publishe

DYNAMIC BALANCING OF FOUR-BAR LINKAGES: A CONVEX OPTIMIZATION FRAMEWORK FOR EFFICIENTLY OBTAINING GLOBALLY OPTIMAL COUNTERWEIGHTS

This paper focusses on reducing the dynamic reactions (shaking force, shaking moment and driving torque) of plane, crank-rocker four-bars through counterweight addition. Determining the mass parameters of the counterweights constitutes an optimization problem, which is classically considered to be nonlinear and hence difficult to solve. A first contribution of this paper is the proof that this optimization problem can be reformulated as a convex program, that is, a nonlinear optimization problem that still has a unique (and hence guaranteed global) optimum, which can be found with great efficiency. Because of the unique features of this formulation, it becomes possible to investigate (and by the guarantee of obtaining a global optimum, in fact prove) the ultimate limits of dynamic balancing, in a reasonable amount of time. When applied to a particular example, this results in design charts, which clearly illustrate (i) the tradeoff between minimizing the different dynamic reactions, and (ii) the fact that adding counterweights is effective, but at the cost of a significant amount of added mass. These design charts constitute a second contribution of the present work