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This paper describes grasp point selection on an item of clothing randomly placed on a table. The input data for our proposed method is a range image captured from a fixed, 3D range camera. Hem elements are extracted from the data, and their relationships are characterized for both similarity measures and grasp point evaluation. Experiments using real images, targeting a piece of clothing, show the...
We synthesize grasping points for planar grasps. We formulate and solve the problem from control theory point of view. Designed control law moves initial arbitrary contact points smoothly from a non force-closure configuration to a closest force-closure one. Control law is independent from the friction coefficient, and it is robust to small changes in shape and pose of the object, and it can track...
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...
The fusion of tactile and visual modalities is crucial for understanding objects and learning how to manipulate them. A common modus operandi in robotics is to deal with each of these modalities separately. We propose an integrated approach that associates to local visual features of an object, tactile feedback of the effector when touching that part of the object. Thus the agent learns to predict...
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 proposes a method for bin-picking for objects without assuming the precise geometrical model of objects. We consider the case where the shape of objects are not uniform but are similarly approximated by cylinders. By using the point cloud of a single object, we extract the probabilistic properties with respect to the difference between an object and a cylinder and consider applying the...
This paper is about grasping known objects of arbitrary shape with a humanoid robot. We extend our previous work, where we presented a grasp planning method using an object representation based on the medial axis transform (MAT). The MAT describes an object's topological skeleton and contains information about local symmetry properties and thickness valuable for grasp planning. So far, our previous...
We address the problem of representations for anthropomorphic robot hands and their suitability for use in methods for learning or control. We approach hand configuration from the perspective of ultimate hand function and propose 2 parameterizations based on the ability of the hand to engage oppositional forces. These parameters can be extracted from grasp examples making them suitable for use in...
This paper presents a novel approach to emptying a basket filled with a pile of objects. Form, size, position, orientation and constellation of the objects are unknown. Additional challenges are to localize the basket and treat it as an obstacle, and to cope with incomplete point cloud data. There are three key contributions. First, we introduce Height Accumulated Features (HAF) which provide an efficient...
Multi-fingered robot grasping is a challenging problem that is difficult to tackle using hand-coded programs. In this paper we present an imitation learning approach for learning and generalizing grasping skills based on human demonstrations. To this end, we split the task of synthesizing a grasping motion into three parts: (1) learning efficient grasp representations from human demonstrations, (2)...
Grasping by Components (GBC) is a very important component of any scalable and holistic grasping system that abstracts point cloud object data to work with arbitrary shapes with no apriori data. Superquadric representation of point cloud data is a suitable parametric method for representing and manipulating point cloud data. Most Superquadrics based grasp hypotheses generation methods perform the...
The grasping skill is an indispensable quality for general service robotics. In a home-like natural environment, manipulated objects may be unknown in advance, which prevents the use of a combination of traditional grasp planning and visual pose estimation to realize grasping. Stereo vision is an inexpensive and relatively general sensor for 3-D objects. However, the quality of the sensor data from...
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