28,007 research outputs found
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Ebubekir Avci, Chanh-Nghiem Nguyen, Kenichi Ohara, Yasushi Mae, Tatsuo Arai, Analysis and suppression of residual vibration in microhand for high-speed single-cell manipulation, International Journal of Mechatronics and Automation, 2013-Vol.3, No.2, pp.110-11
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Time Variant Predictive Control of Autonomous Vehicles: Time Variant Predictive Control of Autonomous Vehicles
This paper develops a linearized time variant model predictive control (MPC) approach for controlling autonomous vehicle tracking on feasible trajectories generated from the vehicle nonlinear ordinary differential equations (ODEs). The paper is an application of the results from computational schemes for nonlinear model predictive control published in (International Journal of Control, Automation and Systems 2011 9(5), 958-965; Mechatronics 2013, Trajectory Generation for Autonomous Vehicles, 615-626, Springer). The vehicle nonlinear dynamic equations are derived and solved in MPC optimizer. Solution for the closed loop control is obtained by solving online the vehicle dynamic ODEs. Simulations for the new schemes are presented and analyse
Encoderless Gimbal Calibration of Dynamic Multi-Camera Clusters
Dynamic Camera Clusters (DCCs) are multi-camera systems where one or more
cameras are mounted on actuated mechanisms such as a gimbal. Existing methods
for DCC calibration rely on joint angle measurements to resolve the
time-varying transformation between the dynamic and static camera. This
information is usually provided by motor encoders, however, joint angle
measurements are not always readily available on off-the-shelf mechanisms. In
this paper, we present an encoderless approach for DCC calibration which
simultaneously estimates the kinematic parameters of the transformation chain
as well as the unknown joint angles. We also demonstrate the integration of an
encoderless gimbal mechanism with a state-of-the art VIO algorithm, and show
the extensions required in order to perform simultaneous online estimation of
the joint angles and vehicle localization state. The proposed calibration
approach is validated both in simulation and on a physical DCC composed of a
2-DOF gimbal mounted on a UAV. Finally, we show the experimental results of the
calibrated mechanism integrated into the OKVIS VIO package, and demonstrate
successful online joint angle estimation while maintaining localization
accuracy that is comparable to a standard static multi-camera configuration.Comment: ICRA 201
A Passivity-based Nonlinear Admittance Control with Application to Powered Upper-limb Control under Unknown Environmental Interactions
This paper presents an admittance controller based on the passivity theory
for a powered upper-limb exoskeleton robot which is governed by the nonlinear
equation of motion. Passivity allows us to include a human operator and
environmental interaction in the control loop. The robot interacts with the
human operator via F/T sensor and interacts with the environment mainly via
end-effectors. Although the environmental interaction cannot be detected by any
sensors (hence unknown), passivity allows us to have natural interaction. An
analysis shows that the behavior of the actual system mimics that of a nominal
model as the control gain goes to infinity, which implies that the proposed
approach is an admittance controller. However, because the control gain cannot
grow infinitely in practice, the performance limitation according to the
achievable control gain is also analyzed. The result of this analysis indicates
that the performance in the sense of infinite norm increases linearly with the
control gain. In the experiments, the proposed properties were verified using 1
degree-of-freedom testbench, and an actual powered upper-limb exoskeleton was
used to lift and maneuver the unknown payload.Comment: Accepted in IEEE/ASME Transactions on Mechatronics (T-MECH
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