Robotic inspection and maintenance are gaining importance due to the number of different scenarios in which robots can operate. The use of robotic systems to accomplish such tasks has deep implications in terms of safety for human workers and can significantly extend the life of infrastructures and industrial facilities. In this context, long-reach cable-driven hyper-redundant robots can be employed to inspect areas that are difficult to reach and hazardous environments such as tanks and vessels. This paper presents a novel long-reach cable-driven hyper-redundant robot called SLIM (Snake-Like manipulator for Inspection and Maintenance). SLIM consists of a robotic arm, a pan and tilt mechanism as end-effector, and an actuation box that can rotate and around which the arm can wrap. The robot has a total of 15 degrees of freedom and, therefore, for the task of positioning the tool centre point in a bi-dimensional Cartesian space with a specific attitude, it has 10 degrees of redundancy. The robot is designed to operate in harsh environments and high temperatures and can deploy itself up to about 4.8 m. This paper presents the requirements that drove the design of the robot, the main aspects of the mechanical and electronic systems, the control strategy, and the results of preliminary experimental tests performed with a physical prototype to evaluate the robot performances.

In this work, supported by the AUTORECON European Project, a highly reconfigurable gripper equipped with vision system for factory automation is described. The gripper has been designed to be dexterous and able to adapt itself to grasp parts within a wide range of shapes and weights. Following a similar strategy, the vision system does not need any database or training. It can be used to manage the grasping of objects that are unknown in advance, regardless from their position or alignment within the working range of the gripper. Before grasping the parts, the vision system automatically detects the position of the object. The optimal grasping points are then deduced by analyzing the geometry features of the part and the actual position and configuration of the fingers of the gripper. The detection and decision on proper grasping points is fast in the order of tens ms, so the whole system can be successfully used even if the parts are swiftly moving on a conveyor.

In electronic manufacturing system, the design of the robotic hand with sufficient dexterity and configuration is important for the successful accomplishment of the assembly task. It is significant that the robot can grasp assembly parts and do some simple in-hand manipulation so as to fit them with the package slots. In this research, we study the process of precise in-hand posture transition problem using a novel jaw like gripper with human-sized anthropomorphic features. We transform the in-hand manipulation problem into a series of static grasping problems. Then we study the successful twisting condition on each grasp frame by analyzing its dynamic performance and requirements. Based on this data-driven idea, simulation and experimental data is obtained from both successful and failed trials. Finally, we create the distribution of parameters grasp map for successful twisting.

This paper describes a general purpose gripper to be used into industrial manufacturing application. The gripper has been developed in the context of the AUTORECON project. It is based on a 2 degrees of freedom finger that is able to adapt itself to objects of various shape, size, material and weight. Thanks to its highly reconfigurable and adaptive capabilities, the gripper described here is an attempt to create a gripper suitable in industrial application to assemble compounds of several different workpieces using only one robot. The high dexterity and the wide range of possible uses of the gripper described here intends to explore a new approach to the design of industrial grippers to be used in factory automation. Moreover, the adaptive capabilities of this gripper make it suitable to grasp workpieces with complicated geometry or highly irregular shape, as it has been proved in performed automotive test rig described here.

In electronic manufacturing system, the design of the robotic hand with sufficient dexterity and configuration is important for the successful accomplishment of the assembly task. Due to the growing demand from high-mix manufacturing industry, it is difficult for the traditional robot to grasp a large number of assembly parts or tools having cylinder shapes with correct postures. In this research, a novel jaw like gripper with human-sized anthropomorphic features is designed for in-hand precise positioning and twisting online. It retains the simplicity feature of traditional industrial grippers and dexterity features of dexterous grippers. It can apply a constant gripping force on assembly parts and performs reliable twisting movement within limited time to meet the industrial requirements. Manipulating several cylindrical assembly parts by robot, as an experimental case in this paper, is studied to evaluate its performance. The effectiveness of proposed gripper design and mechanical analysis is proved by the simulation and experimental results.

A SensAble Omni force feedback device has been modified to increase the face validity of a needle insertion simulation. The new end effector uses a real needle hub and shortened needle shaft in place of the Omni's pre-fitted pen shaped end effector. This modification facilitates correct procedural training through the simulation of co-located visual and haptic cues in an augmented reality approach to simulation. The development of the new end effector is described and a pictorial guide to its manufacture and the fitting process is provided. Initial results from face validation studies bode well for the fidelity of this low cost device.