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This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation...Show More
Tactile manipulation will be essential for automating industrial and service tasks currently done by humans. However, the application of tactile feedback to dexterous manipulation remains a challenging unsolved problem, with robot capabilities lagging far behind those of humans. Here, we present the tactile thumb (TacThumb): a cheap, robust, 3-D-printed optical tactile sensor integrated on the Yal...Show More
Deep Reinforcement Learning (DRL) has shown its capability to solve the high degrees of freedom in control and the complex interaction with the object in the multi-finger dexterous in-hand manipulation tasks. Current DRL approaches lack behavior constraints during the learning process, leading to aggressive and unstable policies that are insufficient for safety-critical in-hand manipulation tasks....Show More
Fingertip-based within-hand manipulation, also called precision manipulation, refers to the repositioning of a grasped object within the workspace of a multifingered robot hand without breaking or changing the contact type between each fingertip and the object. Given a robot hand architecture and a set of assumed contact models, this paper presents a method to perform a gross motion analysis of it...Show More
Tactile sensing is essential for intelligent robot control such as for dexterous manipulation tasks. To provide reliable sensors that can withstand industrial applications, we have developed a soft and thin-film tactile sensor capable of detecting tri-axis force components including normal and shear forces. The thickness of the sensor is 5.5 mm, and the sensor can be easily attached on an end-effe...Show More
Dexterous hand programming is considered to be generally difficult suffering from high degree of freedom. Vision-based manipulation learning provides an efficient way to support automatic programming by human demonstration. However, complex visual perception is tightly coupled with the kinematics structure of dexterous hand in existing solutions, which makes it hard to migrate the developed algori...Show More
The first part of this paper describes the development of a humanoid robot hand based on an endoskeleton made of rigid links connected with elastic hinges, actuated by sheath routed tendons and covered by continuous compliant pulps. The project is called UB Hand 3 (University of Bologna Hand, 3rd version) and aims to reduce the mechanical complexity of robotic end effectors yet maintaining full an...Show More
Remote control of robots is usually used to accomplish complex tasks in unstructured environments that are inaccessible or hazardous for humans (e.g., disaster recovery). Teleoperaton of humanoid robots is commonly achieved by employing motion tracking, which simplifies the complexity of manually controlling by reducing the degrees of freedom (DOF). High-quality demonstrations are also crucial for...Show More
This paper presents a force distribution measurement system to investigate dexterous manipulation of hand. The purpose of this measurement is to find good shape designs not away from the hand easily when the object is dexterously manipulated by hand. To do this, it is necessary to examine the force distribution generating on a contact point between the hand and the object. We have developed the me...Show More
Working in unknown environment has become a fundamental requirement of mobile robot manipulation system. This application scenarios require robots to have some basic capabilities, such as the fast and flexible locomotion, dexterous manipulation, and environmental interaction. However, most studies have only focus on just one of the aspects, which restricts the actual applications. This paper attem...Show More
Most current anthropomorphicrobotic hands can realize part of the human hand functions, particularly for object grasping. However, due to the complexity of the human hand, few current designs target at daily object manipulations, even for simple actions like rotating a pen. To tackle this problem, we introduce a gesture based framework, which adopts the widely-used 33 grasping gestures of Feix as ...Show More
Long-horizon dexterous robot manipulation of deformable objects, such as banana peeling, is a problematic task because of the difficulties in object modeling and a lack of knowledge about stable and dexterous manipulation skills. This article presents a goal-conditioned dual-action deep imitation learning (DIL) approach that can learn dexterous manipulation skills using human demonstration data. P...Show More
Dexterous robotic manipulation refers to the coordination of multiple fingers or manipulators to grasp and manipulate a target object. In past decades, various achievements have been established in dexterous robotic manipulation in the physical world. However, such dexterous ability is rarely found in nano/micro manipulation, which is mainly due to the difficulty in developing actuators and sensor...Show More
Recently, reinforcement learning has led to dexterous manipulation skills of increasing complexity. Nonetheless, learning these skills in simulation still exhibits poor sample-efficiency which stems from the fact these skills are learned from scratch without the benefit of any domain expertise. In this work, we aim to improve the sample efficiency of learning dexterous in-hand manipulation skills ...Show More
Planning robot dexterity is challenging due to the non-smoothness introduced by contacts, intricate fine motions, and ever-changing scenarios. We present a hierarchical planning framework for dexterous robotic manipulation (HiDex). This framework explores in-hand and extrinsic dexterity by leveraging contacts. It generates rigid-body motions and complex contact sequences. Our framework is based on...Show More
Dexterous multifingered hands are the most complex and versatile variants of robotic end effectors. Compared to simpler grippers and underactuated hands, they should be more capable of grasping and, especially, manipulating different objects. This paper explores the relationship between kinematic design and manipulation performance of robotic hands. Some evaluation criteria frequently used by hand...Show More
Dexterous robotic manipulation in unstructured environments can aid in everyday tasks such as cleaning and caretaking. Anthropomorphic robotic hands are highly dexterous and theoretically well-suited for working in human domains, but their complex designs and dynamics often make them difficult to control. By contrast, parallel-jaw grippers are easy to control and are used extensively in industrial...Show More
We propose to learn to generate grasping motion for manipulation with a dexterous hand using implicit functions. With continuous time inputs, the model can generate a continuous and smooth grasping plan. We name the proposed model Continuous Grasping Function (CGF). CGF is learned via generative modeling with a Conditional Variational Autoencoder using 3D human demonstrations. We will first conver...Show More
Intelligent robotic manipulation is a challenging study of machine intelligence. Although many dexterous robotic hands have been designed to assist or replace human hands in executing various tasks, how to teach them to perform dexterous operations like human hands is still a challenge. This motivates us to conduct an in-depth analysis of human behavior in manipulating objects and propose an objec...Show More
This paper newly proposes the four-fingered robot hand with dual turning mechanism where two and two other fingers can independently rotate inner and outer circles with the common center, respectively. Due to this mechanical configuration, it has the particular rotating axis where the manipulation around the axis can be completely decomposed into the velocity control around the axis and the intern...Show More
In this paper, a novel force/torque sensor is presented. The sensor is based on optoelectronic components and therefore its design is relatively simple and reliable. The sensor design make it suitable for the integration in different robotic systems, such as e.g. the fingers of robotic hands. The basic principle and the design of the sensor are described in this paper, along with a specific protot...Show More
Most works in dexterous manipulation consider Force Closure Grasp (FCG), not only for rigid object but also, for flexible ones, though in the second case a force readjustment is also necessary. However, there are situations in which FCG is nonviable. This paper deals with the situation of a flexible object that must be necessarily grasped from one of its sides, taking advantage of its flexibility....Show More
Few years old children lift and manipulate unfamiliar objects more dexterously than todaypsilas robots. Therefore, it has arisen an interest at the artificial intelligence community to look for inspiration on neurophysiological studies to design better models for the robots. The estimation of the friction coefficient of the objectpsilas material is a crucial information in a human dexterous manipu...Show More
The home service robot becomes a new dominant challenge for robotic researches especially for the development of the smart home system. The home service robot are used for nursing care service purposes which also designed to handle multiple types of house tasks such as garment folding. This work considers the problem of recognizing the configuration of the garment that already crudely spread-out o...Show More
This paper presents a vision-based demonstration data collection platform designed to facilitate dexterous robot manipulation for the relocation task. The platform comprises three stages: video capture, pose estimation, and retargeting to the robotic hand, which is then mapped into a simulation environment for behavior learning. To ensure the quality of data for reinforcement learning and imitatio...Show More