This paper presents a design, a control scheme, and experiments for a new vibrating magnet robot (ViMbot). Permanent magnets in the new robot vibrate due to an external vibrating magnetic field. The vibration motion of the robot induces the locomotion of the robot. The vibratory dynamic response of the ViMbot is heavily dependent on the frequency of the vibration. This paper shows that the direction of the robot locomotion can be controlled by the vibration frequency of the external magnetic field. To achieve the distinct dynamic responses depending on the vibration frequency, three acrylic plates with different torsional stiffness are attached at three sides of the triangle-shaped ViMbot and then a magnet is attached to each plate. A strategy to find the special frequencies inducing locomotion and associated experiments with the ViMbot are presented. Control experiments for the ViMbot using the special frequencies are also presented. Because the proposed robot is actuated by an external energy source, the robot can move without traditional actuation components such as motors with batteries. This new design concept allows us to miniaturize the proposed robot.

In this paper we design a robot that can move forward and backward based on the vibration excitation. The proposed design enables the robot to locomote on the horizontal surface using the vibration excitation that is perpendicular to the locomotion direction. The bidirectional locomotion is achieved, and the direction of motion is determined by the vibration frequency. This new type of robot is useful for the unconventional environment where complex moving mechanisms cannot be applied to the robots such as medical, small pipeline, and underwater vehicle applications. To this end, two springs with different stiffness are perpendicularly connected and support the main body of the robot. The dynamic response of this nonlinear system to the vibration enables the robot to walk forward and backward depending on the vibration frequency. The numerical simulation of this system and the experiments with actual hardware design verify the proposed approach.

In this paper, we improve the path-of-probability (POP) algorithm to generate better and smoother paths for robotic systems. The POP algorithm generates a full path with the maximum probability to reach a target. Although the POP algorithm has been successfully applied to path generation of robotic systems, it has the limit that the intermediate paths are generated using a finite and small number of candidate paths. This results in non-smooth (or zigzag pattern) paths which are not desirable for practical use. In addition, this approach sometimes fails to generate a path that reaches a target. This can be overcome by increasing the number of candidate paths, but it increases the computation time too. To improve the POP method, we use a fuzzy logic. The fuzzy logic enables us to obtain a continuous set for the intermediate paths from the discrete candidate paths. By applying it, smoother paths from the starting point to the target can be obtained directly without any additional path smoothing because the intermediate paths are chosen from a continuous set. Fundamentally, the fuzzy logic makes a mapping from a finite and discrete set of candidate paths to a continuous set of paths. We apply the proposed method to path planning for a two wheeled robot and a flexible needle. The simulation results confirm the performance of the proposed approach.

In this paper, we propose a new insertion plan for steerable flexible needles with which we can target multiple locations in the plane with a single entry point (i.e. port). The method is developed based on the observation that multiple locations can be reached by a flexible needle through insertion, partial retraction, rotation, and re-insertion of the needle. We show that in 2D space this problem can be solved using a geometric relationship between multiple tangent circles. Specifically we find a needle insertion point, a corresponding insertion direction and lengths for insertion and retraction with which we can generate the optimal needle trajectory that reaches two or three planar targets with the minimum tissue damage. This minimization problem is solved using exhaustive search of a cost function on the 1D bounded domain. We build a prototype of a needle insertion system and develop C#-based software to compute the optimal needle paths and perform the planned insertion as an open-loop controller. Finally, actual insertion examples are presented.