Previously, a wearable multimodal sensory feedback device (SFD) was developed to communicate proprioceptive information from a robotic gripper onto the operator’s forearm. The SFD showed promise in that it could effectively communicate proprioceptive sensory information and enhance the body’s natural proprioceptive sense. This study delves into the feedback modes implemented into the feedback device by evaluating the effect that increased skin-stretch in combination with vibrotactile stimulation has on the users’ abilities to discern the location of the tactor after time has passed. The SFD used in this study implements a tactor, made of either silicone or foam that translates laterally across the ventral side of the forearm. Subjects were asked to sense the location of the tactor after it had been stationary for a period of time. The experiments’ results indicate that a material that provides increased skin-stretch sensation can benefit the duration of skin-stretch feedback for sensory feedback devices. Additionally, vibrotactile stimulation has shown to be promising though its compatibility with the silicone material was not ideal.

The provision of proprioceptive feedback can be crucial to the use of wearable devices (prostheses) and teleoperated robots. This paper focuses on the development and evaluation of the wearable haptic feedback system capable of displaying proprioceptive information through rotary skin stretch and vibrotactile sensations. An experimental study was conducted to determine how well subjects can perceive skin stretch, applied to the posterior aspect of the upper arm by a rotating end effector, as proprioceptive feedback from a rotary input dial (potentiometer), and whether vibration can improve the accuracy of that proprioception. Results show that with skin stretch feedback, subjects could locate the angle of the input dial to within 5.48 degrees, compared to 5.82 degrees when participants had no feedback (used hand proprioception alone). When considering vibration alone and skin stretch with vibration, accuracy increased to 4.17 degrees and 4.25 degrees, respectively. Though proprioception of input dial angles improved with all forms of feedback, the time to subject determination of the angle increased by as much as 45%, from 4.4 sec to 6.4 sec.

A wearable multimodal sensory feedback device (SFD) was developed to communicate proprioceptive information from a robotic grasper onto the operator’s forearm. The robotic grasper could pick up objects through a pinching motion and was composed of two fingers, each able to open and close in a mirror of the other. The aperture amount of each of the grasper’s fingers was mapped onto the SFD which uses two separate actuators that induced skin-stretch and implemented vibrotactile stimuli to communicate this information to the user. This paper evaluates the extent to which the SFD can effectively communicate the grasper’s proprioceptive information using skin stretch feedback that is maintained with vibrations. Subjects were asked to manipulate the grasper blindly guided by their natural proprioceptive feedback only (NO), their natural proprioceptive feedback and skin-stretch feedback (NS), skin-stretch feedback only (SS), and skin-stretch and vibrotactile stimulation (SV). The experiments’ results indicate that the SFD can effectively communicate proprioceptive sensory information and enhance the body’s natural proprioceptive sense.

The force modulation of robotic manipulators has been extensively studied for several decades. However, it is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees—a large proportion of them concerning the modulation of interaction forces. This study presents a high-level framework for simultaneous trajectory optimization and force control of the interaction between a manipulator and soft environments, which is prone to external disturbances. Sliding friction and normal contact force are taken into account. The dynamics of the soft contact model and the manipulator are simultaneously incorporated in a trajectory optimizer to generate desired motion and force profiles. A constrained optimization framework based on the alternative direction method of multipliers has been employed to efficiently generate real-time optimal control inputs and high-dimensional state trajectories in a model-predictive control fashion. The experimental validation of the model performance is conducted on a soft substrate with known material properties using a Cartesian space force control mode. Results show a comparison of ground truth and real-time model-based contact force and motion tracking for multiple Cartesian motions in the valid range of the friction model. It is shown that a contact-model-based motion planner can compensate for frictional forces and motion disturbances and improve the overall motion and force tracking accuracy. The proposed high-level planner has the potential to facilitate the automation of medical tasks involving the manipulation of compliant, delicate, and deformable tissues.

The fit of a wearable device, such as a prosthesis, can be quantitatively characterized by the mechanical coupling at the user-device interface. It is thought that the mechanical impedance, specifically the stiffness and damping, of wearable device interfaces can significantly impact human performance while using them. To test this theory, we develop a forearm-mounted testbed with a motorized, two degree of freedom (2-DOF) gimbal to simulate variations in the mechanical fit of an upper-extremity wearable device during pointing and target tracking tasks. The two gimbal motors are impedance-controlled to vary the mechanical stiffness and damping between the user and the device's laser pointer end-effector. In this paper, experiments are conducted to determine the torque constants of the motors before implementation in the testbed, and to validate the accuracy of the joint impedance controller. The completed impedance-controlled wearable interface testbed is validated further by comparing the gimbal joint displacements and torques, recorded during 2-DOF base excitation experiments, to MATLAB Simulink simulation data.

Whiskers are widely used by animals for sensing physical interactions with their environments. By combining the Kirigami skin pop-up feature and flexible conducting layer, we designed a deployable Kirigami whisker sensor. The sensor can deploy from a flat state to a sensing state while whisker stiffness and initial pop-up angle can be tuned by adjusting the pre-stretch strain. Preliminary results show that the sensor works well both in air and underwater. The sensor is capable of measuring both externally applied forces and water flow.

Roboticists have increasingly sought to incorporate mechanical compliance into legged robots to realize a range of potential benefits, from improved agility to resilience in complex environments. A promising approach for building compliance into robot legs is to utilize the pneumatic artificial muscle, a pneumatic actuator with inherent compliance due to the compressibility of air. While previous work has explored the capabilities of pneumatic-muscle driven robots in highly dynamic tasks like jumping, there is a lack of trajectory planning strategies for such robots. In this paper, we detail our approach to planning vertical jumping trajectories for a planar two-legged robot driven by four pneumatic artificial muscles using on/off "burst inflation" control. The trajectory optimization problem is represented as a factor graph and solved with the GTSAM optimizer. A hybrid dynamics approach is used to handle foot-ground contacts. The average jump height error between simulation and experiment across multiple jumping trajectories of varying heights was 9.5 cm; the average RMS error between all four joints was 5.6 deg. This work provides a basis to plan more complex jumping and leaping trajectories for pneumatic muscle-driven robots.

This paper discusses the design and preliminary evaluation of a soft pneumatic socket (SPS) with real-time pressure regulation and an automated underactuated donning mechanism (UDM). The ability to modulate the pressure at the human-socket interface of a prosthesis or wearable device to accommodate user's activities has the potential to make the user more comfortable. Furthermore, a hands-free, underactuated donning mechanism designed to reliably and safely don the socket onto the user may increase the convenience of prostheses and wearable devices. The pneumatic socket and donning mechanism are evaluated on synthetic forearm model designed to closely match the mechanical properties of the human forearm. The pneumatic socket was tested to determine the maximum loads it can withstand before slipping and the displacement of the socket after loading. The donning mechanism was able to successfully don the socket on to the replica forearm with a 100% success rate for the 30 trials that were tested. Both devices were also tested to determine the pressures they impart on the user. The highest pressures the socket can impart on the user is 4psi and the maximum pressure the donning mechanism imparts on the user is 0.83psi. These pressures were found to be lower than the reported pressures that cause pain and tissue damage.

Underwater roll rotation is a basic but essential maneuver that allows many biological swimmers to achieve high maneuverability and complex locomotion patterns. In particular, sea mammals (e.g., sea otter) with flexible vertebra structures have a unique mechanism to efficiently achieve roll rotation, not propelled mainly by inter-digital webbing or fin, but by bending and twisting their body.In this work, we attempt to implement and effectively control the roll rotation by mimicking this kind of efficient biomorphic roll mechanism on our two degrees of freedom (DOF) soft modular swimming robot. The robot also allows the achievement of other common maneuvers, such as pitch/yaw rotation and linear swimming patterns. The proposed 2DOF soft swimming robot platform includes an underactuated, cable-driven design that mimics the flexible cascaded skeletal structure of soft spine tissue and hard spine bone seen in many fish species. The cable-driven actuation mechanism is oriented laterally for forwarding motion and steering in a 3D plane. The robot can perform a steady and controllable roll rotation with a maximum angular speed of 41.6 deg/s. A hypothesis explaining this novel roll rotation mechanism is set forth, and the phenomenon is systematically studied at different frequencies and phase lag gait conditions. Preliminary results show a linear relationship between roll angular velocity and frequency within a specific range. Additionally, the roll rotation can be controlled independently in some special conditions. These abilities form the foundation for future research on 3D underwater locomotion with adaptive, controllable maneuvering capabilities.

Force modulation of robotic manipulators has been extensively studied for several decades but is not yet commonly used in safety-critical applications due to a lack of accurate interaction contact modeling and weak performance guarantees - a large proportion of them concerning the modulation of interaction forces. This study presents a high-level framework for simultaneous trajectory optimization and force control of the interaction between manipulator and soft environments. Sliding friction and normal contact force are taken into account. The dynamics of the soft contact model and the manipulator dynamics are simultaneously incorporated in a trajectory optimizer to generate desired motion and force profiles. A constrained optimization framework based on Differential Dynamic Programming and Alternative Direction Method of Multipliers has been employed to generate optimal control inputs and high-dimensional state trajectories. Experimental validation of the model performance is conducted on a soft substrate with known material properties using a Cartesian space force control mode. Results show a comparison of ground truth and predicted model based contact force states for multiple Cartesian motions and the validity range of the friction model. The proposed high-level planning has the potential to be leveraged for medical tasks involving manipulation of compliant, delicate, and deformable tissues.

Recent surges in global construction spending are driving the need for safer, more efficient construction methods. One potential way of improving construction methods is to provide user interfaces that allow human operators to control machinery in a more intuitive and strategic manner. This paper explores the use of motion scaling and haptic feedback to improve task completion speed and force control during construction-related teleoperated robotic manipulation tasks. In this study, we design a bench-top Teleoperated Motion Scaling Robotic Arm (TMSRA) platform that allows the human operator to control the motion-mapping rate between the master (haptic console) and slave (robotic excavator) devices, while also providing force feedback and virtual safety functions to help prevent excessive force application by the slave device. We experimentally evaluated the impact of motion scaling and force feedback on human users' ability to perform simulated construction tasks. Experimental results from simulated robotic excavation and demolition tasks show that the maximum force applied to fictive buried utilities was reduced by 77.67% and 76.36% respectively due to the force feedback and safety function. Experimental results from simulated payload pushing/sliding tasks demonstrate that the provision of user- controlled motion scaling increases task efficiency, reducing completion times by at least 31.41%, and as much as 47.76%.

A low-cost optical sensing method for improved measurement and control of soft pneumatic manipulator motion is presented. The core of a soft continuum robot is embedded with several optically-diffuse elastomer sensors which attenuate light depending on their strain mode and degree. The optical sensors measure local strains at the robot's axial center, and these strain data are combined with measured actuator chamber pressures to determine the pose of the robot under various gravitational and tip loading conditions. Regression analyses using neural networks (NNs) demonstrate that when the soft continuum robot's base orientation is fixed, the position of its end-effector can be estimated with 3.42 times more accuracy (71 % smaller root mean squared error) when using both optical sensor and pressure data (~2.44mm) than when using only pressure data (~8.3mm). When the robot's base orientation was varied, the combined optical sensor and pressure data provide position estimates which are as much as 37.8 times more accurate (~2.76mm) than pressure data alone (~104mm).

Force feedback during robotic surgery is critical in order to minimize potential injury to the patient and decrease recovery time from surgical procedures. Here we describe the use of a novel strain gauge printing method to apply low profile, low cost sensors directly to the surface of da Vinci surgical robot end effectors (Intuitive Surgical, Inc.) to sense deflection and provide force feedback. This additive, vapor-deposition-based sensor fabrication method is used to deposit strain gauges directly onto the surfaces of the end effectors with minimal disruption to the device and without the need for adhesives or machining operations. Initial experiments characterize sensor performance and indicate the applicability of the proposed approach for force feedback during minimally invasive procedures.

This paper presents the design and experimental validation of a soft pneumatic artificial muscle with position and force sensing capabilities. Conductive liquid-based soft sensors are embedded in a fiber-reinforced contractile actuator to measure two modes of deformation - axial strain and diametral expansion - which, together, are used to determine the stroke length and contractile force generated under internal pressure. We validate the proposed device by using data from the embedded sensors to estimate the force output of the actuator at fixed lengths and the stiffness and force output of a one degree-of-freedom hinge joint driven by an antagonist pair of the sensorized pneumatic muscles.

The intrinsic mechanical compliance that makes soft robotic systems ideal for safe, adaptive physical interactions in the presence of uncertainty also poses significant challenges in control. The highly-nonlinear deformations that soft robots undergo are difficult to model and predict, and are even harder to measure and modulate when the soft structures are exposed to complex mechanical loads. This paper presents a method for tracking the deformation modes of soft inflatable bending actuators used in grasp assist devices. Soft strain sensors are designed and strategically placed within the body of a bending actuator to allow measurement of the primary deflection mode - flexion/extension - and measurement of axial twist and lateral deflection modes which are induced by grasping forces. Multimodal bending sensor prototypes were tested independently and embedded in pneumatic bending actuators. Results demonstrated varying levels of measurement accuracy and highlighted the challenges of tracking motion in soft devices. Multimodal sensors were also evaluated in a virtual proprioception experiment and demonstrated efficacy in providing sensory capabilities for human augmentation devices.

This paper demonstrates the use of mechanotactile feedback to provide humans with virtual proprioception of their prosthetic devices. Traditional prostheses provide little or no sensory feedback, requiring the user to visually inspect many tasks performed with device. Virtual proprioception can allow humans to incorporate the kinematic and kinetic states of an external device into their body image, leading to greater physical intuition of device activity, lower cognitive loading, more reliable usage models, and more dexterous manipulation. Vibrotactile stimuli are used the display sensory information about the grasp aperture, grasp force, and object surface texture through a powered split-hook prosthesis. Experimental evaluation of manipulation with mechanotactile-based virtual proprioception strong capability to accurately determine object properties (85.4% success) without need for visual inspection.

This paper presents the design and control of a teleoperated robotic system for dexterous micromanipulation tasks at the meso-scale, specifically open microsurgery. Robotic open microsurgery is an unexplored yet potentially a high impact area of surgical robotics. Microsurgical operations, such as microanastomosis of blood vessels and reattachment of nerve fibers, require high levels of manual dexterity and accuracy that surpass human capabilities. A 3-DoF robotic wrist is designed and built based on a spherical five-bar mechanism. The wrist is attached to a 3-axis commercial off-the-shelf linear stage, achieving a fully dexterous system. Design requirements are determined using motion data collected during a simulated microanastomosis operation. The wrist design is optimized to maximize workspace and manipulability. The system is teleoperated using a haptic device, and has the required bandwidth to replicate microsurgical motions. The system was successfully used in a micromanipulation task to stack 1 mm-diameter metal spheres. The micromanipulation system presented here may improve surgical outcomes during open microsurgery by offering better accuracy and dexterity to surgeons.

The ability to measure human hand motions and interaction forces is critical to improving our understanding of manual gesturing and grasp mechanics. This knowledge serves as a basis for developing better tools for human skill training and rehabilitation, exploring more effective methods of designing and controlling robotic hands, and creating more sophisticated human-computer interaction devices which use complex hand motions as control inputs. This paper presents work on the design, fabrication, and experimental validation of a soft sensor-embedded glove which measures both hand motion and contact pressures during human gesturing and manipulation tasks. We design an array of liquid-metal embedded elastomer sensors to measure up to hundreds of Newtons of interaction forces across the human palm during manipulation tasks and to measure skin strains across phalangeal and carpal joints for joint motion tracking. The elastomeric sensors provide the mechanical compliance necessary to accommodate anatomical variations and permit a normal range of hand motion. We explore methods of assembling this soft sensor glove from modular, individually fabricated pressure and strain sensors and develop design guidelines for their mechanical integration. Experimental validation of a soft finger glove prototype demonstrates the sensitivity range of the designed sensors and the mechanical robustness of the proposed assembly method, and provides a basis for the production of a complete soft sensor glove from inexpensive modular sensor components.

Underactuated compliant robotic hands exploit passive mechanics and joint coupling to reduce the number of actuators required to achieve grasp robustness in unstructured environments. Reduced actuation requirements generally serve to decrease design cost and improve grasp planning efficiency, but overzealous simplification of an actuation topology, coupled with insufficient tuning of mechanical compliance and hand kinematics, can adversely affect grasp quality and adaptability. This paper presents a computational framework for reducing the mechanical complexity of robotic hand actuation topologies without significantly decreasing grasp robustness. Open-source grasp planning software and well-established grasp quality metrics are used to simulate a fully-actuated, 24 DOF anthropomorphic robotic hand grasping a set of daily living objects. DOFs are systematically demoted or removed from the hand actuation topology according to their contribution to grasp quality. The resulting actuation topology contained 22% fewer DOFs, 51% less aggregate joint motion, and required 82% less grasp planning time than the fully-actuated design, but decreased average grasp quality by only 11%.

Stroke is the leading cause of long-term disability in the United States, affecting over 795,000 people annually. In order to regain motor function of the upper body, patients are usually treated by regular sessions with a dedicated physical therapist. A cost-effective wearable upper body orthotics system that can be used at home to empower both the patients and physical therapists is described. The system is composed of a thin, compliant, lightweight, cost-effective soft orthotic device with an integrated cable actuation system that is worn over the upper body, an embedded limb position sensing system, an electric actuator package and controller. The proposed device is robust to misalignments that may occur during actuation of the compliant brace or when putting on the system. Through simulations and experimental evaluation, it was demonstrated i) that the soft orthotic cable-driven shoulder brace can be successfully actuated without the production of off-axis torques in the presence of misalignments and ii) that the proposed model can identify linear and angular misalignments online.

Micromanipulation methods used for complicated tasks such as microrobot assembly and microvascular surgery often lack the force reflection and contact localization capability necessary to achieve robust grasps of micro-scale objects without applying excessive forces. This absence of haptic feedback is especially prohibitive in cases where visual evidence of force application, such as object surface deformation, is imperceptible and where unstructured, dynamically changing environments require force sensing and modulation for safe, atraumatic object manipulation. This paper describes the design, fabrication, and experimental validation of a soft tactile sensor array for sub-millimeter contact localization and contact force measurement during micromanipulation. The geometry and placement of conductive liquid embedded channels within the sensor array are optimized to provide adequate sensitivity for representative micro-manipulation tasks. Mechanical testing of the sensor demonstrates a sensitivity of less than 50mN and contact localization resolution on the order of 100's of microns.

Kinematically redundant manipulators are coveted for their ability to perform more complex and a greater variety of tasks than their non-redundant counterparts. This increased utility demands that manipulator designs be carefully optimized to achieve the kinematic dexterity required to perform their numerous intended tasks. The optimization of redundant manipulator designs to improve isotropy has been studied at great length, but a vast majority of the work done focuses on planar manipulation tasks and workspaces that, unlike many modern manufacturing environments, offer few or no physical impediments to motion. In this paper we investigate the incorporation of secondary manipulation goals, in particular obstacle avoidance, into the calculation of kinematic isotropy measures. We will use these weighted isotropy measures as a performance metric for redundant manipulators working in obstacle-laden workspaces, and employ the metric as part of an objective function for a global search design optimization problem. The effectiveness of the weighted isotropy design optimization will be demonstrated by increasing the global dexterity of a sub-optimal seven degree-of-freedom manipulator design used for pick-and-place tasks within a small, enclosed workspace.