4,356 research outputs found
A nonlinear disturbance observer for robotic manipulators
A new nonlinear disturbance observer (NDO) for robotic manipulators is derived in this paper. The global exponential stability of the proposed disturbance observer (DO) is guaranteed by selecting design parameters, which depend on the maximum velocity and physical parameters of robotic manipulators. This new observer overcomes the disadvantages of existing DOs, which are designed or analyzed by linear system techniques. It can be applied in robotic manipulators for various purposes such as friction compensation, independent joint control, sensorless torque control and fault diagnosis. The performance of the proposed observer is demonstrated by the friction estimation and compensation for a two-link robotic manipulator. Both simulation and experimental results show the NDO works well
Folding Assembly by Means of Dual-Arm Robotic Manipulation
In this paper, we consider folding assembly as an assembly primitive suitable
for dual-arm robotic assembly, that can be integrated in a higher level
assembly strategy. The system composed by two pieces in contact is modelled as
an articulated object, connected by a prismatic-revolute joint. Different
grasping scenarios were considered in order to model the system, and a simple
controller based on feedback linearisation is proposed, using force torque
measurements to compute the contact point kinematics. The folding assembly
controller has been experimentally tested with two sample parts, in order to
showcase folding assembly as a viable assembly primitive.Comment: 7 pages, accepted for ICRA 201
Experimental comparison of parameter estimation methods in adaptive robot control
In the literature on adaptive robot control a large variety of parameter estimation methods have been proposed, ranging from tracking-error-driven gradient methods to combined tracking- and prediction-error-driven least-squares type adaptation methods. This paper presents experimental data from a comparative study between these adaptation methods, performed on a two-degrees-of-freedom robot manipulator. Our results show that the prediction error concept is sensitive to unavoidable model uncertainties. We also demonstrate empirically the fast convergence properties of least-squares adaptation relative to gradient approaches. However, in view of the noise sensitivity of the least-squares method, the marginal performance benefits, and the computational burden, we (cautiously) conclude that the tracking-error driven gradient method is preferred for parameter adaptation in robotic applications
Lightweight design and encoderless control of a miniature direct drive linear delta robot
This paper presents the design, integration and experimental validation of a miniature light-weight delta robot targeted to be used for a variety of applications including the pick-place operations, high speed precise positioning and haptic implementations. The improvements brought by the new design contain; the use of a novel light-weight joint type replacing the conventional and heavy bearing structures and realization of encoderless position measurement algorithm based on hall effect sensor outputs of direct drive linear motors. The description of mechanical, electrical and software based improvements are followed by the derivation of a sliding mode controller to handle tracking of planar closed curves represented by elliptic fourier descriptors (EFDs). The new robot is tested in experiments and the validity of the improvements are verified for practical implementation
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
An alternative control structure for telerobotics
A new teletobotic control concept which couples human supervisory commands with computer reasoning is presented. The control system is responsive and accomplishes an operator's commands while providing obstacle avoidance and stable controlled interactions with the environment in the presence of communication time delays. This provides a system which not only assists the operator in accomplishing tasks but modifies inappropriate operator commands which can result in safety hazards and/or equipment damage
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