Position-Based Control of Under-Constrained Haptics: A System for the Dexmo Glove

Abstract

The Dexmo glove is a haptic exoskeleton that provides kinesthetic feedback in virtual reality. Unlike many other gloves based on string-pulleys, the Dexmo uses a free-hinged link-bar to transfer forces from a crank to the fingertips. It also uses an admittance-based controller parameterized by position, as opposed to an impedance-based controller parameterized by force. When setting the controller's target position, developers must use its native angular coordinate system. The Dexmo has a number of uninstrumented degrees of freedom. Mature forward models can reliably predict the hand pose, even with these unknowns. When it comes to computing angular controller parameters from a target pose in Cartesian space however, things become more difficult. Complex models that provide attractive visuals from a small number of sensors can be non-trivial or even impossible to invert. In this letter, we suggest side-stepping this issue. We sample the forward model in order to build a lookup table. This is embedded in three-dimensional space as a curve, on which traditional queries against world geometry can be performed. Controller parameters are stored as attributes of the sample points. To compute the driver parameters for a target position, the application constrains the position to the geometry, and interpolates them. This technique is generalizable, stable, simple, and fast. We validate our approach by implementing it in Unity 2017.3 and integrating it with a Dexmo glove. Index Terms-Data gloves, force feedback, virtual reality, robot control. I. INTRODUCTION H APTIC feedback extends the immersion of Virtual Environments (VEs) to new sensory modalities. Tactile feedback reproduces surface texture, while force feedback reproduces strain [1]. Haptic interface design is challenging due to the degrees-of-freedom and range-of-motion that must be supported. These lead to conflicting requirements: devices must be stiff but also lightweight; able to apply large forces on demand, but otherwise offer no impedance [2]. Tool-based devices, such as the Phantom Omni, provide high fidelity interaction,

Hands to Hexapods, Wearable User Interface Design for Specifying Leg Placement for Legged Robots

“…There are multiple ways to map finger movement to the robot legs to take into account the differences in kinematics between hands and the robot ( Friston et al, 2019 ; Wang et al, 2019 ; Chen et al, 2015 ; Napier, 1956 ; Taylor and Schwarz, 1955 ; ElKoura and Singh, 2003 ; Haken et al, 1985 ). For the crab robot model used in our lab, the dactyl will be 60% longer than the tibia while human hands have variability in the lengths of the three segments with the last two joints being coupled.…”

“…The second method is to measure finger tip motions. For example, hardware gloves provide haptic feedback at fingertips in Virtual Reality environments ( Gu et al, 2016 ; Friston et al, 2019 ). Here, the component being controlled in virtual reality is not a human hand but a robot leg, and our hypothesis is that having a physical leg model attached to the user’s hand is helpful in improving control efficiency.…”

I-nteract: A cyber-physical system for real-time interaction with physical and virtual objects using mixed reality technologies for additive manufacturing

“…This commercialised version is based on the early prototype reported in [13]. While proprietary basic low-level control laws (inner-loop) have been accomplished by Dexta, research activities are currently on-going to provide a more complete command strategy (outer-loop), either in term of force or position feedback [40].…”

“…The PIP and DIP joints of each digit has only one degree of freedom (DOF). Therefore, the glove has 21 DOF [40]. The actuators (motors) that provide force feedback and the position sensors that capture the fingers motion are installed only at the MCP joints of each digit.…”

An Adaptive Hand exoskeleton for Teleoperation System

“…Furthermore, the exoskeleton only has a tactile detection function and cannot achieve force-sensing reproduction. The force feedback exoskeleton Dexmo [10] [11] developed by Dexta Company could feedback the interaction force from the exoskeleton and its object through a motor with a high gear ratio. However, when the slave hand did not touch the object, it is difficult to simulate the free movement of fingers at low impedance because of the large transmission ratio, which limits the performance of the human hand.…”