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The purpose of this paper is to present a surgical robot for spinal fusion and its control framework that provides higher operation accuracy, greater flexibility of robot position control, and improved ergonomics.

A human‐guided robot for the spinal fusion surgery has been developed with a dexterous end‐effector that is capable of high‐speed drilling for cortical layer gimleting and tele‐operated insertion of screws into the vertebrae. The end‐effector is position‐controlled by a five degrees‐of‐freedom robot body that has a kinematically closed structure to withstand strong reaction force occurring in the surgery. The robot also allows the surgeon to control cooperatively the position and orientation of the end‐effector in order to provide maximum flexibility in exploiting his or her expertise. Also incorporated for improved safety is a “drill‐by‐wire” mechanism wherein a screw is tele‐drilled by the surgeon in a mechanically decoupled master/slave system. Finally, a torque‐rendering algorithm that adds synthetic open‐loop high‐frequency components on feedback torque increases the realism of tele‐drilling in the screw‐by‐wire mechanism.

Experimental results indicated that this assistive robot for spinal fusion performs drilling tasks within the static regulation errors less than 0.1 μm for position control and less than 0.05° for orientation control. The users of the tele‐drilling reported subjectively that they experienced torque feedback similar to that of direct screw insertion.

Although the robotic surgery system itself has been developed, integration with surgery planning and tracking systems is ongoing. Thus, the screw insertion accuracy of a whole surgery system with the assistive robot is to be investigated in the near future.

The paper arguably pioneers the dexterous end‐effector appropriately designed for spinal fusion, the cooperative robot position‐control algorithm, the screw‐by‐wire mechanism for indirect screw insertion, and the torque‐rendering algorithm for more realistic torque feedback. In particular, the system has the potential of circumventing the screw‐loosening problem, a common defect in the conventional surgeon‐operated or robot‐assisted spinal fusion surgery.

The purpose of this paper is to describe research to enable a robust navigation of guide robots in erratic environments with partial sensor information.

Two techniques were developed. One is a robust node discrimination method by using an adaptive sensor matching method. The other is a robot navigation technique with partial sensor information.

A successful navigation was implemented in erratic environments using partial sensor information.

First robot navigation is addressed along the generalized Voronoi graph (GVG) with partial sensor information. A solution is also provided for a phantom node detection problem, which is one of the main defects in GVG navigation.

The paper's purpose is to propose a localization algorithm for topological maps constituted by nodes and edges in a graph form. The focus is to develop a robust localization algorithm that works well even under various dynamic noises.

For robust localization, the authors propose an algorithm which utilizes all available data such as node information, sensor measurements at the current time step (which are used in previous algorithms) and edge information, and sensor measurements at previous time steps (which have not been considered in other papers). Also, the algorithm estimates a robot's location in a multi‐modal manner which increases its robustness.

Findings show that the proposed algorithm works well in topological maps with various dynamics which are induced by the moving objects in the map and measurement noises from cheap sensors.

Unlike previous approaches, the proposed algorithm has three key features: usage of edge data, inclusion of history information, and a multi‐modal based approach. By virtue of these features, the paper develops an algorithm that enables robust localization performance.