Rescue Robots play an important role during rescue missions in disasters such as 9/11, which caused more than 2,000 deaths and thousands of injuries. However, tele-operating rescue robots are unable to perform their tasks constantly due to the limitation of current wireless communication technology. Therefore, rescue robots with the capability of performing their tasks autonomously during temporarily lost connections to the control base would be ideal. This paper introduces our development of a semi-autonomous rough terrain robot for rescue missions. The robot's hardware components, system architecture, and software architecture are described in order to provide a general overview of our robot. An alternative and comprehensive map-generating algorithm is presented and discussed. Finally, experimental setup and results from a testing arena are reported.Index Terms -rescue robot, rough terrain robot, semiautonomous robot, mobile robot, path planning, SLAM

Minimally invasive surgery (MIS) is one of the most challenging tasks in surgical procedures due to the lack of visibility of the surgical area, instrument orientation, and depth perception. A tele-operated robot assisted minimally invasive surgery is developed to enhance a surgeon's hand dexterity and accuracy. To perform MIS, the surgeon controls a slave manipulator via a master manipulator, so the force feedback and motion feedback are required to imitate an amount of action and reaction force between master and slave manipulator. The complicated MIS requires more complex surgical manipulator with multi DOFs and multiple force feedback. The limitation of multiple DOFs force feedback is a bandwidth of torque sensors. Therefore, this study proposes a sensorless based 5-DOF Bilaterally controlled surgical manipulation. In this research disturbance observer (DOB) is used to identify the internal disturbance of the system, which is used to estimate the reaction torque. This research mainly focuses on a 5-DOF bilaterally controlled surgical manipulator to maintain a position and additional force. The result of torque error in contact motion is less than 2%, the non-contact motion error is not over 5%, and it is evident that the error is always less than 0.3% for the position response.

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<span>Distal locking procedure is one of the most complex tasks in close intramedullary nailing operation which requires fluoroscopic image to interpret 2-D distal locking position on image related to 3-D distal locking position on the patient site. Hence the surgeon has to perform the distal locking process by using multiple fluoroscopic images which causes a lot of x-ray exposure to the patient and surgeon and is a time consuming task. This paper presents the system integration of a fluoroscopic image calibration using robot assisted surgical guidance. The system integration consists of three parts; distal locking recovery, fluoroscopic calibration and tracking, and robot assisted surgical guidance. The distal locking-hole recovery algorithm is based on characteristic information of the major and minor axes of distal locking hole. The fluoroscopic calibration and tracking is modeled as pin-hole projection model to estimate a projection equation based on optical tracking system. The robot-assisted surgical guidance is developed to overlay a trajectory path using a laser beam for reducing the problem of hand – eye coordination on most surgical navigation system. We integrate each part to complete a surgical navigation system for distal locking process. The experiment of system integration is conducted to validate the accuracy of distal locking axis position and orientation. The results of the system integration shows a mean angular error of 1.10 and mean Euclidean distance in X-Y plane error of 3.65 mm.</span>

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