Integrated high pressure microhydraulic actuation and control for surgical instruments

To reduce the surgical trauma to the patient, minimally invasive surgery is gaining considerable importance since the eighties. More recently, robot assisted minimally invasive surgery was introduced to enhance the surgeon's performance in these procedures. This resulted in an intensive research on the design, fabrication and control of surgical robots over the last decades. A new development in the field of surgical tool manipulators is presented in this article: a flexible manipulator with distributed degrees of freedom powered by microhydraulic actuators. The tool consists of successive flexible segments, each with two bending degrees of freedom. To actuate these compliant segments, dedicated fluidic actuators are incorporated, together with compact hydraulic valves which control the actuator motion. Especially the development of microvalves for this application was challenging, and are the main focus of this paper. The valves distribute the hydraulic power from one common high pressure supply to a series of artificial muscle actuators. Tests show that the angular stroke of the each segment of this medical instrument is 90°. © 2012 Springer Science+Business Media, LLC.

Behavior learning of a face robot based on the characteristics of human instruction

Computer simulation experiments were performed to examine the effectiveness of OR- and comparative-reinforcement learning algorithms. In the simulation, human rewards were given as +1 and -1. Two models of human instruction that determine which reward is to be given in every step of a human instruction were used. Results show that human instruction may have a possibility of including both model-A and model-B characteristics, and it can be expected that the comparative-reinforcement learning algorithm is more effective for learning by human instructions.

A quality-guided displacement tracking algorithm for ultrasonic elasticity imaging.

Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.

A species conserving genetic algorithm for multimodal function optimization

This paper introduces a new technique called species conservation for evolving parallel subpopulations. The technique is based on the concept of dividing the population into several species according to their similarity. Each of these species is built around a dominating individual called the species seed. Species seeds found in the current generation are saved (conserved) by moving them into the next generation. Our technique has proved to be very effective in finding multiple solutions of multimodal optimization problems. We demonstrate this by applying it to a set of test problems, including some problems known to be deceptive to genetic algorithms.

Component-based approach to the holonic control of a robot assembly cell

The aim of this paper is to describe the implementation of a new approach for the introduction of so called 'holonic manufacturing' principles into existing production control systems. Such an approach is intended to improve the reconfigurability of the control system to cope with the increasing requirements of production change. A conceptual architecture is described and implemented in a robot assembly cell to demonstrate that this approach can lead to a manufacturing control system which can adapt relatively simply to long-term change. A design methodology and migration strategy for achieving these solutions using conventional hardware is proposed to develop execution level of manufacturing control systems.