Garments with the ability to provide kinesthetic force-feedback on-demand can augment human capabilities in a non-obtrusive way, enabling numerous applications in VR haptics, motion assistance, and robotic control. However, designing such garments is a complex, and often manual task, particularly when the goal is to resist multiple motions with a single design. In this work, we propose a computational pipeline for designing connecting structures between active components—one of the central challenges in this context. We focus on electrostatic (ES) clutches that are compliant in their passive state while strongly resisting elongation when activated. Our method automatically computes optimized connecting structures that efficiently resist a range of pre-defined body motions on demand. We propose a novel dual-objective optimization approach to simultaneously maximize the resistance to motion when clutches are active, while minimizing resistance when inactive. We demonstrate our method on a set of problems involving different body sites and a range of motions. We further fabricate and evaluate a subset of our automatically created designs against manually created baselines using mechanical testing and in a VR pointing study.

Abstract Kinesthetic garments provide physical feedback on body posture and motion through tailored distributions of reinforced material. Their ability to selectively stiffen a garment's response to specific motions makes them appealing for rehabilitation, sports, robotics, and many other application fields. However, finding designs that distribute a given amount of reinforcement material to maximally stiffen the response to specified motions is a challenging problem. In this work, we propose an optimization‐driven approach for automated design of reinforcement patterns for kinesthetic garments. Our main contribution is to cast this design task as an on‐body topology optimization problem. Our method allows designers to explore a continuous range of designs corresponding to various amounts of reinforcement coverage. Our model captures both tight contact and lift‐off separation between cloth and body. We demonstrate our method on a variety of reinforcement design problems for different body sites and motions. Optimal designs lead to a two‐ to threefold improvement in performance in terms of energy density. A set of manufactured designs were consistently rated as providing more resistance than baselines in a comparative user study.

We introduce an optimal control method for electromagnetic haptic guidance systems. Our real-time approach assists users in pen-based tasks such as drawing, sketching or designing. The key to our control method is that it guides users, yet does not take away agency. Existing approaches force the stylus to a continuously advancing setpoint on a target trajectory, leading to undesirable behavior such as loss of haptic guidance or unintended snapping. Our control approach, in contrast, gently pulls users towards the target trajectory, allowing them to always easily override the system to adapt their input spontaneously and draw at their own speed. To achieve this flexible guidance, our optimization iteratively predicts the motion of an input device such as a pen, and adjusts the position and strength of an underlying dynamic electromagnetic actuator accordingly. To enable real-time computation, we additionally introduce a novel and fast approximate model of an electromagnet. We demonstrate the applicability of our approach by implementing it on a prototypical hardware platform based on an electromagnet moving on a bi-axial linear stage, as well as a set of applications. Experimental results show that our approach is more accurate and preferred by users compared to open-loop and time-dependent closed-loop approaches.

We introduce TacTiles, light (1.8g), low-power (130 mW), and small form-factor (1 cm3) electromagnetic actuators that can form a flexible haptic array to provide localized tactile feedback. Our novel hardware design uses a custom 8-layer PCB, dampening materials, and asymmetric latching, enabling two distinct modes of actuation: contact and pulse mode. We leverage these modes in Virtual Reality (VR) to render continuous contact with objects and the exploration of object surfaces and volumes with spatial haptic patterns. Results from a series of experiments show that users are able to localize feedback, discriminate between modes with high accuracy, and differentiate objects from haptic surfaces and volumes even without looking at them.

Wearables are increasingly used during training to quantify performance and provide valuable real-time information. However, interacting with these devices in motion may disrupt the movements of the activity. We propose a method of interaction involving tapping specific locations on the body, identify candidate locations for running and cycling, and compare them in a series of controlled experiments with athletes. A purpose-built prototype measures speed of interaction and gives feedback cues for athletes to report the physical effects on the activity itself. Our results suggest that specific locations are faster and have minimal disruption to movement, even under induced fatigue conditions. The overall method is fast - 1.31s for running and 1.65s for cycling. Preferred locations differ significantly across sports, with stable body parts ranking higher. We effectively demonstrated the use of a single hand for interaction during running with two distinct tap gestures. A set of guidelines inform the design of new sports technologies.

We introduce DextrES, a flexible and wearable haptic glove which integrates both kinesthetic and cutaneous feedback in a thin and light form factor (weight is less than 8g). Our approach is based on an electrostatic clutch generating up to 20 N of holding force on each finger by modulating the electrostatic attraction between flexible elastic metal strips to generate an electrically-controlled friction force. We harness the resulting braking force to rapidly render on-demand kinesthetic feedback. The electrostatic brake is mounted onto the the index finger and thumb via modular 3D printed articulated guides which allow the metal strips to glide smoothly. Cutaneous feedback is provided via piezo actuators at the fingertips. We demonstrate that our approach can provide rich haptic feedback under dexterous articulation of the user's hands and provides effective haptic feedback across a variety of different grasps. A controlled experiment indicates that DextrES improves the grasping precision for different types of virtual objects. Finally, we report on results of a psycho-physical study which identifies discrimination thresholds for different levels of holding force.

We present Follow-My-Lead, an alternative indoor navigation technique that uses visual information recorded on an actual navigation path as a navigational guide. Its design revealed a trade-off between the fidelity of information provided to users and their effort to acquire it. Our first experiment revealed that scrolling through a continuous image stream of the navigation path is highly informative, but it becomes tedious with constant use. Discrete image checkpoints require less effort, but can be confusing. A balance may be struck by adding fast video transitions between image checkpoints, but precise control is required to handle difficult situations. Authoring still image checkpoints is also difficult, and this inspired us to invent a new technique using video checkpoints. We conducted a second experiment on authoring and navigation performance and found video checkpoints plus fast video transitions to be better than both image checkpoints plus fast video transitions and traditional written instructions.

We present MagTics, a novel flexible and wearable haptic interface based on magnetically actuated bidirectional tactile pixels (taxels). MagTics' thin form factor and flexibility allows for rich haptic feedback in mobile settings. We propose a novel actuation mechanism based on bistable electromagnetic latching that combines high frame rate and holding force with low energy consumption and a soft and flexible form factor. We overcome limitations of traditional soft actuators by placing several hard actuation cells, driven by flexible printed electronics, in a soft 3D printed case. A novel EM-shielding prevents magnet-magnet interactions and allows for high actuator densities. A prototypical implementation comprising of 4 actuated pins on a 1.7 cm pitch, with 2 mm travel, and generating 160 mN to 200 mN of latching force is used to implement a number of compelling application scenarios including adding haptic and tactile display capabilities to wearable devices, to existing input devices and to provide localized haptic feedback in virtual reality. Finally, we report results of a psychophysical study, conducted to inform future developments and to identify possible application domains.