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.

Liquid-phase detection of biological targets utilizing magnetic marker and superconducting quantum interference device (SQUID) magnetometer is shown. In this method, magnetic markers are coupled to the biological targets, and the binding reaction between them is detected by measuring the magnetic signal from the bound markers. Detection can be done in the liquid phase, i.e., we can detect only the bound markers even in the presence of unbound (free) markers. Since the detection principle is based on the different magnetic properties between the free and bound markers, we clarified the Brownian relaxation of the free markers and the Neel relaxation of the bound markers. Usefulness of the present method is demonstrated from the detection of the biological targets, such as biotin-coated polymer beads, IgE and Candida albicans.