Wearable fingertip haptic devices aim to deliver somatosensory feedback for applications such as virtual reality, rehabilitation, and enhancing hardware/physical control interfaces. However, providing various kinds of feedback requires several Degrees of Freedom (DoF) and high mechanical complexity which are mechanically difficult to achieve at the mesoscale. Using compliant low-profile transmissions embedded in an origami structure and PCBmotors as actuators, we designed and fabricated a novel 3-DoF fingertip haptic device, called Haptigami. This under-actuated system, measuring 36 x 25 x 26 mm and weighing 13 g, can render vibrotactile and cutaneous force feedback. We tested our device by creating a novel experimental protocol and robotic platform allowing quantitative characterization of mechanical performance. The current prototype of Haptigami produces 678 mN in compression, and 400 mN and 150 mN in shear for the Y and X directions respectively. By virtue of its unique origami-inspired design, Haptigami brings a new direction for future designs of lightweight and compact wearable robots.

Series elastic actuators (SEAs) and variable elastic actuators (VSAs) provide shock resistance, energy storage, and stable force control. However, they usually require extra springs, mechanical parts, and transmissions, increasing size, weight, number of moving parts, and reducing the mechanical efficiency. In particular, this mechanical complexity is one of the significant challenges in the design of wearable and scalable force feedback devices. In this article, flexure variable stiffness actuators (F‐VSAs), which combine kinematic transmission, elasticity, and stiffness modulation via a network of folding patterns using flexure hinges, are presented. Thus, F‐VSAs allow the creation of robots benefiting from the advantages of SEAs and VSAs without hindering form factor or mechanical efficiency. To illustrate the design strategy of F‐VSAs, a 4‐design‐of‐freedom (DoF) robot that provides stiffness and force output is presented. An analytical model that estimates the inherent stiffness and the end‐effector force output for any given configuration of the folding pattern is proposed. Finally, stiffness modulation and force control of the robot are implemented and good agreement with the predictions from the model is observed. Thus, this novel design strategy allows the creation of compact and scalable robots with stiffness and force output for wearable, rehabilitation, and haptic applications.

Accurate spatiotemporal alignment of multi-view video streams is essential for a wide range of dynamic-scene applications such as multi-view 3D reconstruction, pose estimation, and scene understanding. However, synchronizing multiple cameras remains a significant challenge, especially in heterogeneous setups combining professional- and consumer-grade devices, visible and infrared sensors, or systems with and without audio, where common hardware synchronization capabilities are often unavailable. This limitation is particularly evident in real-world environments, where controlled capture conditions are not feasible. In this work, we present a low-cost, general-purpose synchronization method that achieves millisecond-level temporal alignment across diverse camera systems while supporting both visible (RGB) and infrared (IR) modalities. The proposed solution employs a custom-built LED Clock that encodes time through red and infrared LEDs, allowing visual decoding of the exposure window (start and end times) from recorded frames for millisecond-level synchronization. We benchmark our method against hardware synchronization and achieve a residual error of 1.34 ms RMSE across multiple recordings. In further experiments, our method outperforms light-, audio-, and timecode-based synchronization approaches and directly improves downstream computer vision tasks, including multi-view pose estimation and 3D reconstruction. Finally, we validate the system in large-scale surgical recordings involving over 25 heterogeneous cameras spanning both IR and RGB modalities. This solution simplifies and streamlines the synchronization pipeline and expands access to advanced vision-based sensing in unconstrained environments, including industrial and clinical applications.

Robotic origami design allows creating meso-scale robotic systems and mechanisms not limited by degrees of freedom, miniaturization and assembly downsides of conventional transmission mechanisms. However, unlike the traditional rigid approaches, robotic origami application has been limited by the complex deformation and kinematics of the compliant joints and actuation based on active materials or conventional electric motors. To generalize their application at meso-scale requires a combination of the predictability of traditional rigid kinematics and the manufacturing flexibility of robotic origami. Here we present a study of conventional transmission mechanisms, including a slider-crank and cam-follower, made in quasi-2D form by selective machining and stacking of multiple layers of composite material with minimal assembly. Owing to a compliant design powered by low-profile piezoelectric motors, our 5.3 mm thick and lightweight mechanisms transmit rotational motion to translational movements in and out-of-plane. We develop analytic models that we validate in terms of force and motion output on our prototypes.

Purpose: Markerless inside-out surgical instrument tracking using a tool-mounted camera offers a promising solution to the limited clinical adoption of the existing navigation systems, which primarily rely on outside-in optical tracking and are constrained by line-of-sight issues. However, its performance in the surgical environment, with its unique challenges, remains largely unexplored. This work benchmarks state-of-the-art inside-out methods, namely, visual Simultaneous Localization and Mapping (vSLAM) methods. To this end, we collected a first-of-its-kind dataset in spine endoscopy, providing ground-truth tool poses. Methods: We recorded endoscopic spine surgeries performed on a high-fidelity training model in a real operating room environment, containing synchronized stereo images from tool-mounted cameras, sub-millimetric ground truth pose data from a commercial optical tracking system, and the endoscopic feed. Using this dataset, the instrument tracking accuracy of a selected number of vSLAM algorithms was compared. Results: The best performing approach achieved a root mean squared absolute trajectory error of 2.0 mm and 1.47 degrees, reaching accuracies of around 1 mm and 1 degree on selected sequences. However, it shows degraded performance in the presence of challenges such as occlusions and scene-object dynamics. Conclusions: Markerless inside-out tracking using vSLAM demonstrated high accuracy, indicating potential feasibility for navigated endoscopic spine applications. Our evaluation revealed that current algorithms remain insufficiently robust for routine clinical use. The presented study and dataset establish a foundation for future research toward reliable, real-time inside-out navigation in minimally invasive surgery.