gjie Yin

Hybrid control of multi-fingered robot hand for dexterous manipulation

Human hand can not only catch and grasp the complex objects but also easily manipulate the objects by switching various types of interactions. Research on the basic mechanics and control principles of hands dexterous manipulation abilities is one of the most important subjects in bio-mimetics. In this paper, we formalize the multi-fingered hand manipulation problem as a general dynamic complementarity (DC) system. Based on the fact that the DC system can be transformed to a mixed logical dynamical (MLD) model, and that MLD system can control problem can be solved using powerful mixed integer programming (MIP) algorithm, we propose to realize dexterous hand manipulations by using a cyber-grasp system, and study its robotic realization on GIFU hand III, which is equipped with tactile sensors. We suggest that in order to obtain sub-optimal solutions, biologically inspired techniques might be very powerful.

Mixed Logic Dynamical Modeling and On Line Optimal Control of Biped Robot

Human being can decide his walking to auto-adapt to environment changes. Comparing with this, the autonomy of biped robots is inefficient or remains unsolved. One basic reason for this is the less of a unified modeling framework for various types of biped motion in varying environment which allows on-line deriving of the control input In this paper, we propose to recast types of biped motion in the framework of hybrid system, express it as a mixed logic dynamical model. Such a point of view possesses the advantage that it encompasses all the motions (such as single support motion and impact phenomenon) into a unique one, thus allow the control system to be design optimally even though the impact occurs as the interior point of the optimization horizon

Hybrid System Modeling and Control of Multi-contact Hand Manipulation

Human hand can not only catch and grasp the complex objects but also easily manipulate the objects by switching various types of interactions. Research on the basic mechanics and control principles of hands dexterous manipulation abilities is one of the most important subjects in biomimetics. In this paper, by considering the multicontact manipulation problem as a hybrid one, we propose a modeling framework which encapsulates switching between phases of continuous motion. The presentation is illustrated by a typical example, multicontact whole finger manipulation problem, where in addition to the continuous part the event driven component should be carefully designed. We first formulates the robot hand subject to unilateral constraints into a general dynamic complementarity (DC) system expression, then transform DC system to a mixed logical dynamical (MLD) model. Based on the derived MLD model dexterous finger manipulation can be realized via mixed integer quadric programming (MIQP) algorithm. Further more, MLD model can be expected for subsequent stability and control studies, which is still missing in the field of multicontact robot system design by taking into account the whole hybrid dynamics

A nonlinear adaptive robust control design for robotic systems under time-varying parameter perturbation and external disturbance

Many control strategies have been proposed to compensate for uncertainties of robotic system, where the uncertain parameters are assumed to be constant. However, this assumption may not be satisfied in practice. In this paper, we consider the tracking problem for robot manipulator with unknown and time-varying physical parameters and disturbances. Our proposed state feedback adaptive robust controller consists of a nonlinear compensation based on nominal physical parameters, a linear and a nonlinear state feedback, and an adaptation algorithm for adjustment of the gravitational parameters. The effects of time-varying parameters and disturbances on the tracking performance can be attenuated within a prescribed level. Exact asymptotic tracking can be achieved for set point control with vanishing disturbances and constant parameters. By adding feedback input to penalty variable, high gain feedback can be strategically avoided. The effectiveness of the proposed method is verified by simulation and experiments.

Tracking control of the continuous and discrete hybrid systems

It is known that the motor control system of a human is a natural hybrid system. A human uses his predictive function based on an internal model together with feedback junction for motion tracking, which is considered as a motor control model of a cerebellum. However, in control engineering field, the understanding of hybrid systems control is rather limited at present. The system theoretic studies such as analysis of controllability and trackability are very few in literature. In this study, we consider the tracking control problem of hybrid plants represented by MLD model to follow a family of reference signals produced by an external generator. New algorithms are presented. The internal model principle of continuous system is extended to hybrid systems so as to solve the problem.

MLD modeling and optimal control of hand manipulation

In this paper, by taking a multi-contact planar manipulation system as an example, we propose a modeling and control approach based on hybrid system theory, whereby a dexterous manipulation task is formulated as a mixed logic dynamical (MLD) model. A model predictive control (MPC) is used to handling the control objectives of MLD system, which can be solved using powerful mixed integer quadric programming (MIQP) algorithm. The validation of the proposed approach is shown by simulation.

MLD Modeling and MPC of Hand Manipulation

Based on hybrid system theory, we propose a modeling and control approach for a multi-contact planar manipulation system, whereby a dexterous manipulation task is formulated as a mixed logic dynamical (MLD) model. The MLD model provides the possibility of carrying out the selection of modes, the timing for mode switching, and the determination of the continuous control input simultaneously in a systematical way. Model predictive control (MPC) is adopted for the synthesis of the dexterous hand manipulation system. The solution of the MPC can be found by using mixed integer quadric programming (MIQP) algorithm, and corresponds to the optimal motion of the hand manipulation. The validation of the proposed approach is shown by some simulation results.

Modeling and control of multifingered robot hand for dexterous manipulation: a continuous and discrete hybrid approach

By considering the dexterous multi-fingered manipulation problem as a hybrid one, we at first propose a MLD model which encapsulates occurrence of impacts, switching between types of contact motion, and phases of continuous motion. Then we deal with planning and tracking problem of the derived MLD system, propose to realize dexterous hand manipulation via MIQP. The effectiveness of the proposed approach is validated by simulation results

A hybrid external system for the generation of biped locomotion

For the gait pattern planning of a biped running, we proposed a hybrid external system for the periodic orbit generation. Comparing with traditional motion planning methods where the trajectories were approximated by polynomials, our proposal is more general and systematic. The manifold of initial state and the selection of parameters of the external system are addressed. The output of the hybrid external system corresponds to the periodic trajectory of joints. The hybrid external system is robust to state disturbance. Basing on the nonlinear regulation theory, the biped robot can be controlled to asymptotically track the hybrid external system.

Synthesis of biped locomotion from view point of hybrid systems

The objective of this study is to analyze and synthesize a hybrid system for the systematic generation of biped locomotion. The structure, the manifold of initial state, and the selection of parameters of the hybrid system are addressed. The output of the hybrid system corresponds to the periodic trajectory of joint positions of the biped robot, which can be designed piecewise arbitrary smoothly. Comparing with the traditional numerical methods for gait planning, where the joint trajectory is approximated by polynomial, our proposal is systematic and analytic. The variation of the trajectory caused by perturbation of the initial state of the reference generator can be predicted. Then according to the nonlinear output regulation theory, the biped robot can be controlled to asymptotically track the periodic gait generated by the hybrid external system.