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Current self-adaptive hands are always complex in mechanical structure and they have only fixed grasping mode and cannot be adjusted easily. To overcome these disadvantages, this paper proposed a novel scheme of making use of close loop in lower controller to fulfill coupled and self-adaptive grasp. A 2-DOF Electronic Coupled and Self-adaptive finger, E-COSA finger was designed in this paper. E-COSA...
Grasping has always been a hot topic in multidisciplinary field-anatomy, neuroscience and robotics. Recent research on robotic hand grasping has concentrated on introducing the grasp mechanism and characteristics of human hand to robotic hand. This paper analyzes the problem of generating grasp configurations for given objects. A one-step grasp synthesis is applied to a 20DoF five-finger anthropomorphic...
In this paper, we present a system to learn manipulation motion primitives from human demonstration. This system, based on the statistical model “Mimesis Model”, provides an easy-to-use human-interface for learning manipulation motion primitives, as well as a natural language interface allowing human to modify and instruct robot motions. The human-demonstrated manipulation motion primitives are initially...
The rehabilitation quality of stroke patients has drawn much attention in recent years. Researchers have developed various kinds of devices for lower and upper limb rehabilitation functions. In this paper, we present a 3 degrees-of-freedom (3-DOF) wearable robotic fingers for rehabilitation of task-oriented training in grasping tasks. A control strategy is proposed for grasping task training by considering...
The handling of twist-locks has been a heavy burden for the container industry. There have been many efforts in developing automated twist-lock handling solutions. To address this challenge, we are developing a customized mobile manipulator for twist-lock pose estimation and grasping. In this paper, we propose a 3D object recognition approach using Kernel Principal Component Analysis (KPCA) only based...
In this paper we present a method for the generation of hand postural synergies for different precision grasp types to be used in dextrous robot hands. Our method records the robot hand motions while teleoperated by human subjects via a dataglove, doing different grasp types on a series of objects. This exploits the fact that humans automatically compensate for calibration errors on the glove to robot...
We propose a novel approach to transfer reach and grasp movements while being agnostic and invariant to finger kinematics, hand configurations and relative changes in object dimensions. We exploit a novel representation based on electrostatics to parametrise the salient aspects of the demonstrated grasp. By working in this alternate space that focuses on the relational aspects of the grasp rather...
The ability to learn is essential for robots if they are to function within human environments. Learning requires an understanding of the underlying structure of what has been observed. This paper proposes a learning method that automatically creates Petri nets from observation of human demonstrations to model the underlying structure of tasks. The Petri net can be learned via a single or multiple...
This paper presents a novel methodology for planning the movements of a robotic hand when a precision grasp wants to be performed. This approach is based on the standard Fast Marching Square (FM2) path planning method recently introduced for robot formations. A three-finger kinematic chain is consider as a robot formation to perform simulations. In order to achieve a precision grasp, the task is divided...
Light modular mechanical arm is widely used in service robots. This paper combines the SHUNCK 7 DOF mechanical arm in the application of nursing robot, building its kinematics model, analyzing the inverse kinematic problem with the geometry method against specific grasping task, and the dynamic problem with the Newton-Euler method to achieve the smooth movement of the terminal. At last, construct...
Underactuation represents a solution to reduce the number of Degrees of Freddom (DoF) of robotic hands. Altough reducing the number of DoFs in general limits the ability to perform many and different types of grasp, the use of springs in the structure improves the compliance of the grasp and mitigates the loss of generality due to the reduction of DoFs in the mechanical structure. The use of active...
In this paper, we present a novel camera-projector system for assisting robot-human interaction. The system is comprised of a stereo camera pair and a DLP projector. The proposed system provides feedback information indicating the robot's perception of the environment and what action a human user desires. Feedback is delivered by iteratively spotlighting objects in the environment using the projector...
SynGrasp is a MATLAB toolbox developed for the analysis of grasping, suitable both for robotic and human hands. It includes functions for the definition of hand kinematic structure and of the contact points with a grasped object. The coupling between joints induced by an underactuated control can be modeled. The hand modeling allows to define compliance at the contact, joint and actuator levels. The...
Solving complex robot manipulation tasks requires to combine motion generation on the geometric level with planning on a symbolic level. On both levels robotics research has developed a variety of mature methodologies, including geometric motion planning and motion primitive learning on the motor level as well as logic reasoning and relational Reinforcement Learning methods on the symbolic level....
Precise kinematic forward models are important for robots to successfully perform dexterous grasping and manipulation tasks, especially when visual servoing is rendered infeasible due to occlusions. A lot of research has been conducted to estimate geometric and non-geometric parameters of kinematic chains to minimize reconstruction errors. However, kinematic chains can include non-linearities, e.g...
“Grasping by caging” has been considered as a powerful tool to deal with uncertainty. In this paper, we continue to explore into “grasping by caging” and propose a new solution by using eigen-shapes and space mapping. For one thing, eigen-shapes fix dexterous hands into a series of finger formations and help to reduce dimensionality and computational complexity. For the other, space mapping builds...
When an object is caged by a set of fingers, it cannot move arbitrarily far from the caging fingers regardless of what possible rigid motion it takes. Although this condition makes caging an attractive choice for nonprehensile manipulation, directly computing caging configurations is still a complex process. More importantly, using a cage could be too restrictive than necessary in many real cases...
We present a real-world robotic agent that is capable of transferring grasping strategies across objects that share similar parts. The agent transfers grasps across objects by identifying, from examples provided by a teacher, parts by which objects are often grasped in a similar fashion. It then uses these parts to identify grasping points onto novel objects. We focus our report on the definition...
The perception of the surrounding world depends on noisy sensors which introduce uncertainty. When we develop algorithms for grasping with robotic hands it is not enough to assume the best estimate of the environment - if there is a measure of uncertainty we need to account for it. This paper presents a control law which augments a grasp controller with the ability to prefer known or unseen regions...
This paper presents a tool aimed at the design of compliant, under-actuated hands. The particular motivation is hands that will be used for an underwater robot to grasp a variety of objects, some of which may be delicate or slippery. The focus of the analysis is the problem of object acquisition. In comparison to many prior grasp analysis tools, the tool presented here models the dynamics of a hand,...
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