Single-Motor Robotic Gripper With Three Functional Modes for Grasping in Confined Spaces

This study proposes a novel robotic gripper driven by a single motor. The main task is to pick up objects in confined spaces. For this purpose, the developed gripper has three operating modes: grasping, finger-bending, and pull-in modes. Using these three modes, the developed gripper can rotate and translate a grasped object, i.e., can perform in-hand manipulation. This in-hand manipulation is effective for grasping in extremely confined spaces, such as the inside of a box in a shelf, to avoid interference between the grasped object and obstacles. To achieve the three modes using a single motor, the developed gripper is equipped with two novel self-motion switching mechanisms. These mechanisms switch their motions automatically when the motion being generated is prevented. An analysis of the mechanism and control methodology used to achieve the desired behavior are presented. Furthermore, the validity of the analysis and methodology are experimentally demonstrated. The gripper performance is also evaluated through the grasping tests

Manipulability Measures taking Necessary Joint Torques for Grasping into consideration

This paper presents new manipulability measures to evaluate how much easily the robot manipulates the grasped object, simultaneously taking how much magnitude of joint torque we need to keep grasping into consideration. For the purpose, we use operation range. The operation range is for actuator attached to every joint of robot and provides generable joint torque and velocity and their relation (between generating torque/velocity and addable velocity/torque). While we introduced a manipulability measure using the operation range in our previous paper, it was for a limited class due to large computational effort and we could not evaluate whole space of object velocity and could not consider whole space of external wrench. This paper proposes new manipulability measures which can evaluate whole space of object velocity, taking the effect of external wrench in whole space into consideration. ©2010 IEEE

Softness Effects on Manipulability and Grasp Stability

This paper presents a novel analysis for the effects of softness at the fingertip on the manipulability and stability of grasping. The stability for grasping can be regarded that how much magnitude of external wrench we can balance. We formulate manipulability and the set of generable object wrenches for grasping system, taking deformation of the fingertips into consideration, and show that the increase of the softness decreases the manipulability while it increases generable object wrench. The validity of our analysis is shown by numerical examples. © 2011 IEEE

Effect of visual cues on line drawing performance

This paper investigates how visual cues affect human performance at a line drawing task. Line drawing is a primitive and fundamental task using tools such as pens, (soldering) irons, and cutters. Many situations (for example, home, office, studio, and workshop) require drawing lines with tools. Assistive tools for improving performance might be especially useful for unskilled people. As a first step, we focus on visual cues as assistive tools and determine the kinds of visual cues that are effective for good performance. We asked subjects to draw a line on a displayed dotted line while the spacing and shape of the dots is changed, and we then analyzed the data. The results indicate that the cue that should be displayed for good performance should change according to subjects\u27 performance: for good performers the cue whose geometrical center is easy to detect, and for not-good performers the cues whose occupied area is large. We also discussed the possibility of controlling performance in line drawing, and presented a strategy for displaying visual cues for good line drawing performance. © 2013 IEEE

Development of a Multi-fingered Robot Hand with Softness-changeable Skin Mechanism

This paper develops a multi-fingered robot hand with skin mechanism enabling softness change. We show how the softness of the skin affects grasping and manipulation. Elastic skin provides stable grasping while precise manipulation is lost. Hard skin provides precise manipulation while stability of grasp is lost. We will try to change the softness of the skin according to situation, object, and so on. In this paper, we develop a novel human like robot hand with softnesschangeable skin mechanism

Experimental investigation of effect of fingertip stiffness on friction while grasping an object

In this study, we experimentally investigated the effect of robot fingertip stiffness on friction during grasping of an object. To make robots more human-friendly, robotic hands with soft surfaces have been developed. A soft fingertip, i.e., one with low stiffness, is considered desirable because it produces high friction. However, in our experiments, we were able to obtain high friction from a stiff fingertip under a certain condition. We initially investigated the maximum resistible force when solid objects with different angled surfaces were grasped by spherical fingertips of different stiffness. When the contact surface was flat, a stiffer fingertip produced larger frictional force. When the contact surface was highly convex, the maximum frictional force increased with decreasing fingertip stiffness. Secondly, we examined the relationships among the contact area, the load, and the maximum frictional force. We reformulated the relationship between the load and the maximum frictional force and, together with our experimental results, used it to determine the factor that increased the maximum frictional force. © 2014 IEEE.2014 IEEE International Conference on Robotics and Automation, ICRA 2014; Hong Kong Convention and Exhibition CenterHong Kong; China; 31 May 2014 through 7 June 2014; Category numberCFP14RAA-ART; Code 10739

The effect of behavioral preferences on skill acquisition in determining unspecified, suitable action patterns to control humanoid robots

This research investigated the effect of behavioral preferences on learning efficiency when attempting to determine unspecified, but suitable action sequences for unfamiliar tasks. The goal of this research was to develop a skill acquisition support system for the elderly to aid them in using unfamiliar IT products, particularly those of welfare systems. Here, behavioral preference is defined as the type of action sequences that people would prefer to adopt for completing unfamiliar tasks. To achieve this goal, this research investigated the action sequences of participants when they attempt to control the posture of an unfamiliar humanoid robot with an unfamiliar controller. The participants were assigned the task of making the humanoid stand on one foot. Machine-learning-based methods were presented for analyzing the behavioral preferences. The analysis results indicate that participants having behavioral preferences of adopting random action sequences can complete the task in a much shorter time, compared to participants having a behavioral preference of adopting action sequences similar to those of previous actions. © 2015 IEEE.37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015; MiCo Center, Milano Congressi CenterMilan; Italy; 25 August 2015 through 29 August 2015; Category numberCFP15EMB-ART; Code 11680

Grasp input optimization taking contact position and object information uncertainties into consideration

This paper presents a novel approach for grasp optimization considering contact position and object information uncertainties. In practice, it is hard to grasp an object at the designated or planned contact positions, as errors in measurement, estimation, and control usually exist. Therefore, we first formulate the influences of contact uncertainties on joint torques, contact wrenches, and frictional condition. We then include external wrench uncertainties in the required external wrenches set. Based on this formulation, we define the linear grasp optimization problem for two kinds of frictional contact modelsfrictional point contact and soft finger contactso that we can successfully grasp an object even if deviations in contact point, object weight, and center of mass occur. The validity of our approach is shown by means of numerical examples and the result of experiments. © 2004-2012 IEEE

Grasp Motion Planning for box opening task by multi-fingered hands and arms

The aim of our project is to develop a robot to manipulate an object in human environment. In this paper, as a first step, we focus on opening paper box such as tea box, and present a method to plan grasp motion by 2 arms with multi-fingered hands. we propose a task priority based scheme to plan grasping area consistent with whole steps of the given task procedure. Based on the grasping area and the concept of preshape, we derive desired fingertip positions and hand base position and orientation for preshape. Based on the vector field approach, we propose a motion planning method for the planned grasp by multi-fingered hands to avoid any undesired collisions. This method can be applied to regrasping and a motion in which collision is required