Christopher D. W. Ward

Scheduling active camera resources for multiple moving targets

Five scheduling policies that have been developed and implemented to manage the active resources of a centralized active vision system are presented in this paper. These scheduling policies are tasked with making target-to-camera assignments in an attempt to maximize the number of targets that can be imaged with the systems active cameras. A comparative simulation-based evaluation has been performed to investigate the performance of the system under different target and system operating parameters for all five scheduling policies. Parameters considered include: target entry conditions, congestion levels, target-to-camera speeds, target trajectories, and number of active cameras. An overall trend in the relative performance of the scheduling algorithms was observed. The Least System Reconfiguration and Future Least System Reconfiguration scheduling policies performed the best for the majority of conditions investigated, while the Load Sharing and First Come First Serve policies performed the poorest. The performance of the Earliest Deadline First policy was highly dependent on target predictability.

The WHaSP: A Wireless Hands-Free Surgical Pointer for Minimally Invasive Surgery

To address the challenges of surgical instruction during minimally invasive surgery (MIS), a wireless hands-free pointer system has been developed. The Wireless Hands-free Surgical Pointer system incorporates infrared and inertial tracking technologies to address the need for hands-free pointing during MIS. The combination of these technologies allows for optimal movement of the pointer and excellent accuracy while the user is located at a realistic distance from the surgical monitor. Several experimental evaluations were performed to optimize the settings of the sensors, and to validate the system when compared to a commercially available hands-free pointing system. The results show improved performance with the proposed technology as measured by the total trajectory travelled by the pointer and the smoothness of the curve. The technology presented has the potential to significantly improve surgical instruction and guidance during MIS.

A 7-DOF haptics-enabled teleoperated robotic system: Kinematic modeling and experimental verification

The purpose of this paper is to demonstrate the development of a novel 7-degree-of-freedom teleoperated robotic system that provides force reflection to the surgeons hands while performing minimally invasive surgery and therapy (MIST). An endoscopic tool has been sensorized and modified for use as the end effector of this haptics-enabled system. In this paper, mathematical models required for controlling the main components of the system have been determined and experimentally validated. Several experiments have been performed with this MIST robotic system in order to compare its force exertion capabilities with those of the da Vinci system from Intuitive Surgical Inc. Force reflection from the slave to the master in the new system is also demonstrated experimentally.

Computer Vision Based Autonomous Robotic System for 3D Plant Growth Measurement

Research on increasing the production of crops is increasingly important these days. This research needs a way to quantitatively measure the 3D growth of plants under controlled environments to allow a cost versus benefits analysis. Plant scientists need a non-invasive, non-destructive method to quantitatively measure the 3D growth of plants. Traditional methods, for example, measuring weight, area or volume, often negatively affects the future plant growth. Also the manual nature of this measurement can be quite time consuming, tedious and error prone. Some recent effort have been reported in the literature about the construction of autonomous systems for plant phenotype, but these are not practical for large scale accurate 3D plant growth computation. To the best of our knowledge, we are the first in the world to attempt truly 3D approach via robot assisted plant growth analysis using 3D imaging and laser scanning technology. We describe an automated system to perform 3D plant modelling using a laser scanner mounted on a robot arm to capture 3D plant data. We present a detailed overview of the system integration, including the robotic arm, laser scanner and a programmable growth chamber. We also show some results on reconstructing the 3Dmodel of a growing plant which is better than the current state of the art.

A compactmodular active vision system formulti-target surveillance

This paper presents an omnidirectional active vision system that has been developed for the autonomous acquisition of detailed images of multiple targets. Omnidirectional and perspective camera technologies are integrated to create a robust vision system that combines the strengths of both camera types. A compact, inexpensive and highly modular design is presented in which system modules are stacked vertically. The vertical structure provides each module with an unobstructed 360 degree horizontal view of the surroundings and allows the omnidirectional cameras to directly guide an active camera to view a target point. The physical system design is detailed, along with a description of the systems hardware and software architectures. The hardware architecture is scalable and fully self contained, while the software architecture is built around a user datagram protocol (UDP) network, allowing the computational load to be distributed over multiple computers.

Adaptive neural Preisach model and model predictive control of Shape Memory Alloy actuators

Shape memory alloy (SMA) actuators are potential alternatives to conventional actuators in many surgical, aeronautic and biorobotic applications. However, their highly nonlinear hysteretic behavior between temperature and strain makes them difficult to use in real-time applications. The Preisach model is a well-known phenomenological method to accurately model the hysteresis of many physical system. In this paper, the numerical Preisach model is modified such that it can adapt to changes in the operating conditions, and can easily be used in real-time for controlling the strain in the SMA actuators. For this purpose, both the first-order descending and ascending curves are used and each of these curves is approximated by an artificial neural network (ANN). Weights of the ANNs are then updated online using the extended Kalman filter algorithm. To control the strain in the SMA actuator, a model predictive controller is implemented that uses the temperature dynamics and the adaptive modified Preisach model to calculate the optimal control signal using the Levenberg-Marquardt algorithm. Performance of the proposed model and the control scheme are validated using an experimental setup.

Mastery Learning – does the method of learning make a difference in skills acquisition for robotic surgery?

Few studies compare the effectiveness of blocked vs random practice conditions in minimally invasive surgery training, and none have evaluated these in robotic surgery training.

Design of an ultra thin strain sensor using superelastic nitinol for applications in minimally invasive surgery

This paper introduces a novel ultra thin strain sensor made of superelastic nitinol wire that is well suited for force sensing applications of surgical instruments. The sensing principle used for the described sensor is the same as that for conventional strain gauges; however, the proposed sensor has significant advantages of thinner size (15 μm diameter), higher gauge factor (3.5), large strain measurement range (up to 4.25%), lower cost and easier installation process. To validate its force sensing capability for minimally invasive surgical instruments, the sensor was mounted on a da Vinci surgical tool to measure the lateral forces acting at the distal end. Experimental results showed that the sensor can accurately measure forces with an RMS error of 32 mN and with a resolution of 55 mN.