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
Developing natural control strategies represents an intriguing challenge in the design of Human-Robot Interface (HRI) systems. The teleoperation of robotic grasping devices, especially in industrial, rescue and aerospace applications, is mostly based on non-intuitive approaches, such as remote controllers. On the other hand, recent research efforts target solutions that mimic the human ability to manage multi-finger grasps and finely modulate grasp impedance. Since electromyography (EMG) contains information about human motion control, it is possible to leverage such neuromuscular knowledge to teleoperate robotic hands for grasping tasks. In this article we present a HRI system based on 8 fully-differential EMG sensors connected to a wearable sensor node for acquisition and processing.By virtue of a novel bio-inspired approach, the embedded myocontroller merges pattern recognition and factorization techniques to combine a natural selection of the robotic hand configuration with the proportional control of the related grasps. The HRI system has been fully designed, implemented and tested on two robotic hands: a dexterous anthropomorphic hand and a three-fingered industrial gripper mounted on a robotic manipulator. Results of the test performed on 4 able-bodied subjects show success rates greater than 90% reached in grasping objects that require different hand shapes and impedance regulations for the task completion. The outcomes also show that the users modulate the bio-inspired degrees of control in a natural manner, proving the pertinence of the proposed system for an effective human-like control of robotic grasping devices in a wearable form-factor.
Autonomous Underwater Vehicles are frequently used for survey missions and monitoring tasks, however manipulation and intervention tasks are still largely performed with a human in the loop.Employing autonomous vehicles for these tasks has received a growing interest in the last ten years, and few pioneering projects have been funded on this topic. Among these projects, the Italian MARIS project had the goal of developing technologies and methodologies for the use of autonomous Underwater Vehicle Manipulator Systems in underwater manipulation and transportation tasks. This work presents the developed control framework, the mechatronic integration, and the project's final experimental results on floating underwater intervention.Index Terms underwater vehicle manipulator system; underwater gripper; underwater vision; floating underwater control; task priority control; underwater intervention.
In this paper, the design and experimental evaluation of a cable driven robotic gripper for underwater applications is presented. The gripper has three fingers and is characterised by a large workspace if compared with other similar devices reported in literature. Its kinematic configuration allows to execute both parallel and precision grasps on objects with very different dimensions. The gripper has 8 degrees of freedom actuated by only three motors by means of a suitable coupling of the joints obtained through the cable transmission. Moreover, in order to facilitate the execution of complex tasks, special force/torque sensors are mounted on the fingertips. The paper reports the main specifications deriving from the particular tasks in which the gripper is involved, and illustrates the proposed design solutions. Results obtained from real underwater experiments are provided as well, in order to demonstrate the capabilities of the gripper.
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