Latest Papers

ASME Journal of Mechanisms and Robotics

  • Measurement Configuration Optimization and Kinematic Calibration of a Parallel Robot
    by Huang C, Xie F, Liu X, et al. on December 10, 2021 at 12:00 am

    AbstractThis paper presents the kinematic calibration of a four-degrees-of-freedom (4DOF) high-speed parallel robot. In order to improve the calibration effect by decreasing the influence of the unobservable disturbance variables introduced by error measurement, a measurement configuration optimization method is proposed. Configurations are iteratively selected inside the workspace by a searching algorithm, then the selection results are evaluated through an index associated with the condition number of the identification Jacobian matrix; finally, the number of optimized configurations is determined. Since the selection algorithm has been shown to be sensitive to local minima, a meta-heuristic method has been applied to decrease this sensibility. To verify the effectiveness of the algorithm and kinematic calibration, computation validations, pose error estimations, and experiments are performed. The results show that the identification accuracy and calibration effect can be significantly improved by using the optimized configurations.

Control and Control Allocation for Bimodal, Rotary Wing, Rolling–Flying Vehicles

Abstract

This paper presents a robust method for controlling the terrestrial motion of a bimodal multirotor vehicle that can roll and fly. Factors influencing the mobility and controllability of the vehicle are explored and compared to strictly flying multirotor vehicles; the differences motivate novel control and control allocation strategies that leverage the non-standard configuration of the bimodal design. A fifth-order dynamic model of the vehicle subject to kinematic rolling constraints is the basis for a nonlinear, multi-input, multi-output, sliding mode controller. Constrained optimization techniques are used to develop a novel control allocation strategy that minimizes power consumption while rolling. Simulations of the vehicle under closed-loop control are presented. A functional hardware embodiment of the vehicle is constructed onto which the controllers and control allocation algorithm are deployed. Experimental data of the vehicle under closed-loop control demonstrate good performance and robustness to parameter uncertainty. Data collected also demonstrate that the control allocation algorithm correctly determines a thrust-minimizing solution in real-time.
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