TacFR-Gripper: A Reconfigurable Fin Ray-Based Compliant Robotic Gripper with Tactile Skin for In-Hand Manipulation

This paper introduces the TacFR-Gripper, a reconfigurable Fin Ray-based soft and compliant robotic gripper equipped with tactile skin, which can be used for dexterous in-hand manipulation tasks. This gripper can adaptively grasp objects of diverse shapes and stiffness levels. An array of Force Sensitive Resistor (FSR) sensors is embedded within the robotic finger to serve as the tactile skin, enabling the robot to perceive contact information during manipulation. We provide theoretical analysis for gripper design, including kinematic analysis, workspace analysis, and finite element analysis to identify the relationship between the gripper's load and its deformation. Moreover, we implemented a Graph Neural Network (GNN)-based tactile perception approach to enable reliable grasping without accidental slip or excessive force. Three physical experiments were conducted to quantify the performance of the TacFR-Gripper. These experiments aimed to i) assess the grasp success rate across various everyday objects through different configurations, ii) verify the effectiveness of tactile skin with the GNN algorithm in grasping, iii) evaluate the gripper's in-hand manipulation capabilities for object pose control. The experimental results indicate that the TacFR-Gripper can grasp a wide range of complex-shaped objects with a high success rate and deliver dexterous in-hand manipulation. Additionally, the integration of tactile skin with the GNN algorithm enhances grasp stability by incorporating tactile feedback during manipulations. For more details of this project, please view our website: https://sites.google.com/view/tacfr-gripper/homepage

Master of Science

thesisTraditionally, hand rests are used to reduce muscle fatigue and to improve precision in small-workspace dexterous tasks. Dynamic hand rests have been shown to be beneficial for large-workspace planar tasks. However, providing high-bandwidth support in the vertical direction proves to be more challenging than in the horizontal plane. One must decouple the gravitational support of the arm from the intended vertical motion of the user. A vertically moving device, called the Vertical Active Handrest (VAHR), is presented in this thesis. This device dynamically supports the weight of the user's arm over a large workspace to add stability for precision dexterous tasks while providing gravitational support to the arm to reduce fatigue. The goal in developing the VAHR is to integrate its capabilities with the current Active Handrest, which provides dynamic support in the horizontal plane, thus creating a three degree-of-freedom active support device. The VAHR takes control inputs from a force sensor embedded in its armrest and from the tracked position of a tool. Studies were conducted with a variety of controllers and user input strategies to evaluate the VAHR's effectiveness at assisting participants in a single-axis tracking task. An initial pilot test with the VAHR shows no statistical improvements in tracking performance using force input control modes over conditions in which the arm is unsupported, or is supported by a static rest surface. The main experiment presented in this thesis focuses on either pure stylus position input or a combination of position and force inputs. Tracking accuracy significantly improves compared to the unsupported condition while using stylus position input control. Poor performance under pure force control is attributed to the required activation of large muscle groups in the arm to provide force input to the VAHR's instrumented armrest. These large muscle groups are poorly suited for the agile tracking task used for experimentation. It is theorized that the better performance when using the stylus position control modes is because inputs from smaller, more dexterous muscle groups in the hand are utilized, allowing the position of the arm to be controlled by muscles that are already adept at precision control

Doctor of Philosophy

dissertationHumans generally have difficulty performing precision tasks with their unsupported hands. To compensate for this difficulty, people often seek to support or rest their hand and arm on a fixed surface. However, when the precision task needs to be performed over a workspace larger than what can be reached from a fixed position, a fixed support is no longer useful. This dissertation describes the development of the Active Handrest, a device that expands its user's dexterous workspace by providing ergonomic support and precise repositioning motions over a large workspace. The prototype Active Handrest is a planar computer-controlled support for the user's hand and arm. The device can be controlled through force input from the user, position input from a grasped tool, or a combination of inputs. The control algorithm of the Active Handrest converts the input(s) into device motions through admittance control where the device's desired velocity is calculated proportionally to the input force or its equivalent. A robotic 2-axis admittance device was constructed as the initial Planar Active Handrest, or PAHR, prototype. Experiments were conducted to optimize the device's control input strategies. Large workspace shape tracing experiments were used to compare the PAHR to unsupported, fixed support, and passive moveable support conditions. The Active Handrest was found to reduce task error and provide better speedaccuracy performance. Next, virtual fixture strategies were explored for the device. From the options considered, a virtual spring fixture strategy was chosen based on its effectiveness. An experiment was conducted to compare the PAHR with its virtual fixture strategy to traditional virtual fixture techniques for a grasped stylus. Virtual fixtures implemented on the Active Handrest were found to be as effective as fixtures implemented on a grasped tool. Finally, a higher degree-of-freedom Enhanced Planar Active Handrest, or E-PAHR, was constructed to provide support for large workspace precision tasks while more closely following the planar motions of the human arm. Experiments were conducted to investigate appropriate control strategies and device utility. The E-PAHR was found to provide a skill level equal to that of the PAHR with reduced user force input and lower perceived exertion

Doctor of Philosophy

dissertationMost humans have difficulty performing precision tasks, such as writing and painting, without additional physical support(s) to help steady or offload their arm's weight. To alleviate this problem, various passive and active devices have been developed. However, such devices often have a small workspace and lack scalable gravity compensation throughout the workspace and/or diversity in their applications. This dissertation describes the development of a Spatial Active Handrest (SAHR), a large-workspace manipulation aid, to offload the weight of the user's arm and increase user's accuracy over a large three-dimensional workspace. This device has four degrees-of-freedom and allows the user to perform dexterous tasks within a large workspace that matches the workspace of a human arm when performing daily tasks. Users can move this device to a desired position and orientation using force or position inputs, or a combination of both. The SAHR converts the given input(s) to desired velocit

SCALER: Versatile Multi-Limbed Robot for Free-Climbing in Extreme Terrains

This paper presents SCALER, a versatile free-climbing multi-limbed robot that is designed to achieve tightly coupled simultaneous locomotion and dexterous grasping. Although existing quadruped-limbed robots have shown impressive dexterous skills such as object manipulation, it is essential to balance power-intensive locomotion and dexterous grasping capabilities. We design a torso linkage and a parallel-serial limb to meet such conflicting skills that pose unique challenges in the hardware designs. SCALER employs underactuated two-fingered GOAT grippers that can mechanically adapt and offer 7 modes of grasping, enabling SCALER to traverse extreme terrains with multi-modal grasping strategies. We study the whole-body approach, where SCALER uses its body and limbs to generate additional forces for stable grasping with environments, further enhancing versatility. Furthermore, we improve the GOAT gripper actuation speed to realize more dynamic climbing in a closed-loop control fashion. With these proposed technologies, SCALER can traverse vertical, overhang, upside-down, slippery terrains, and bouldering walls with non-convex-shaped climbing holds under the Earth's gravity

IMECE2009-12972 WORKSPACE AND SINGULARITY CHARACTERISTICS OF 3-DOF PLANAR PARALLEL ROBOTS

ABSTRACT A study of workspace and singularity characteristics is presented for two common types of 3-DOF planar parallel robot manipulators. The robots considered feature a kinematic structure with 3 in-parallel actuated, R-R-R and R-P-R serial chain geometries. In this study, computer simulations aided with graphic visualization were used to characterize the complete pose workspace (for ranges of both position and orientation) and the singularity inherent to the systems. Parametric studies have also been performed to ascertain the way in which both characteristics vary with respect to various geometric parameters such as pivot location, link length, and platform size for end-effector. Results are shown by way of a unique composite ratio of the available workspace to the density of singularity within that workspace