Design and Evaluation of FBG-Based Tension Sensor in Laparoscope Surgical Robots

Due to the narrow space and a harsh chemical environment in the sterilization processes for the end-effector of surgical robots, it is difficult to install and integrate suitable sensors for the purpose of effective and precise force control. This paper presents an innovative tension sensor for estimation of grasping force in our laparoscope surgical robot. The proposed sensor measures the tension of cable using fiber gratings (FBGs) which are pasted in the grooves on the inclined cantilevers of the sensor. By exploiting the stain measurement characteristics of FBGs, the small deformation of the inclined cantilevers caused by the cable tension can be measured. The working principle and the sensor model are analyzed. Based on the sensor model, the dimensions of the sensor are designed and optimized. A dedicated experimental setup is established to calibrate and test the sensor. The results of experiments for estimation the grasping force validate the sensor.

The DEXMART hand: Mechatronic design and experimental evaluation of synergy-based control for human-like grasping

This paper summarizes recent activities carried out for the development of an innovative anthropomorphic robotic hand called the DEXMART Hand. The main goal of this research is to face the problems that affect current robotic hands by introducing suitable design solutions aimed at achieving simplification and cost reduction while possibly enhancing robustness and performance. While certain aspects of the DEXMART Hand development have been presented in previous papers, this paper is the first to give a comprehensive description of the final hand version and its use to replicate human-like grasping. In this paper, particular emphasis is placed on the kinematics of the fingers and of the thumb, the wrist architecture, the dimensioning of the actuation system, and the final implementation of the position, force and tactile sensors. The paper focuses also on how these solutions have been integrated into the mechanical structure of this innovative robotic hand to enable precise force and displacement control of the whole system.

Another important aspect is the lack of suitable control tools that severely limits the development of robotic hand applications. To address this issue, a new method for the observation of human hand behavior during interaction with common day-to-day objects by means of a 3D computer vision system is presented in this work together with a strategy for mapping human hand postures to the robotic hand. A simple control strategy based on postural synergies has been used to reduce the complexity of the grasp planning problem. As a preliminary evaluation of the DEXMART Hand’s capabilities, this approach has been adopted in this paper to simplify and speed up the transfer of human actions to the robotic hand, showing its effectiveness in reproducing human-like grasping.

Control strategies for the index finger of a tendon-driven hand

To understand how versatile dexterity is achieved in the human hand and to achieve it in a robotic form, we have constructed an anatomically correct testbed (ACT) hand. This paper focuses on the development of control strategies for the index finger motion and implementation of joint passive behavior in the ACT hand. A direct muscle position control and a force-optimized joint control are implemented for position tracking through muscle force control. The relationships between the muscle and joint motions play a critical role in both of the controllers and we implemented a Gaussian process regression technique to determine these relationships. Our experiments demonstrate that the direct muscle position controller allows for fast position tracking, while the force-optimized joint controller allows for the exploitation of actuation redundancy in the finger critical for this redundant system. We demonstrate that by implementing a passive force–length relationship at each muscle we are able to precisely match joint stiffness of the metacarpophalangeal (MCP) joint of the ACT to that of a human MCP joint. We also show the results from improved position tracking when implemented in the presence of passive muscle control schemes. The control schemes for position tracking and passive behavior are inspired by human neuromuscular control, and form the building blocks for developing future human-like control approaches.