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SUMMARYBionic engineering has been a focus in the field of robotic researches. Inverse dynamic analysis is significant for the determination of dynamic parameters of bionic robots. The present paper uses a newly developed robot modular named Sambot to construct a caterpillar robotic mechanism, and designs a gait of trapezoidal wave locomotion for it. Two open-link models are put forth to simulate the dynamic behavior of such a locomotion. The inverse dynamic differential equations are derived by Kane's method and are then solved numerically by the Runge–Kutta method of the fourth order. Based on the numerical solutions of these differential equations, the applied joint torques required to produce the harmonic trapezoidal wave locomotion are determined finally, providing us important information on the gait control of the caterpillar robotic mechanism. Finally, the theoretical values of the joint torques are applied onto the present caterpillar mechanism to perform a locomotion experiment, which verifies the effectiveness of the present dynamics analysis.

SUMMARYCentral Pattern Generators (CPGs) can generate robust, smooth and coordinated oscillatory signals for locomotion control of robots with multiple degrees of freedom, but the tuning of CPG parameters for a desired locomotor pattern constitutes a tremendously difficult task. This paper addresses this problem for the generation of fish-like swimming gaits with an adaptive CPG network on a multi-joint robotic fish. Our approach converts the related CPG parameters into dynamical systems that evolve as part of the CPG network dynamics. To reproduce the bodily motion of swimming fish, we use the joint angles calculated with the trajectory approximation method as teaching signals for the CPG network, which are modeled as a chain of coupled Hopf oscillators. A novel coupling scheme is proposed to eliminate the influence of afferent signals on the amplitude of the oscillator. The learning rules of intrinsic frequency, coupling weight and amplitude are formulated with phase space representation of the oscillators. The frequency, amplitudes and phase relations of the teaching signals can be encoded by the CPG network with adaptation mechanisms. Since the Hopf oscillator exhibits limit cycle behavior, the learned locomotor pattern is stable against perturbations. Moreover, due to nonlinear characteristics of the CPG model, modification of the target travelling body wave can be carried out in a smooth way. Numerical experiments are conducted to validate the effectiveness of the proposed learning rules.

SUMMARYThe common serial robot or parallel robot is difficult to implement for CT-guided surgery in a limited workspace. A novel hybrid robot with 9 degrees of freedom is presented in this paper, whose detailed structure is analysed based on screw theory and displacement manifold (DM). The dexterity of the hybrid robot is provided in terms of Riemann manifold (RM). Besides, DICOM (digital imaging communications in medicine) image processing, spatial registration and 3D dynamic reconstruction in the operation planning subsystem are analysed, in which some innovative methods are introduced. Meanwhile, the architecture of the CT-guided hybrid robot system and its subsystems are proposed. Simulative clinical experiment showed that the locating precision of the hybrid robot reaches 1.08 mm, which can meet the requirement of CT-guided surgery.