Cynthia Sung

Folding flexible printed circuitboards (FPCBs) into origami patterns offers a route to fabricating robots with actuation, sensing, and control fully integrated into the robot body. However, integrating electronics into origami robots introduces a coupled electrical and mechanical design problem since the circuit layout affects the local stiffness and mass distribution and therefore the deformation mechanics. We explore this problem in the context of the FPCB CurveQuad, a centimeter‐scale curved‐crease origami quadruped. The robot body is fabricated as a folded double‐sided FPCB that contains the crease pattern, copper routing, sensors, local stiffening features, and electrical interfaces. A single servomotor drives tendons on the underside of the body, enabling the sheet to self‐fold from a planar state and twist for crawling and steering. The resulting robot is 60 mm 65 mm 50 mm in the folded state and weighs 10.9 g. It crawls at 16.8 mm (0.259 body lengths ), steers by shifting the actuator oscillation range, and is capable of feedback control. We present our design process for this robot, illustrating strategies for addressing electromechanical co‐design with complex bending requirements, enabling folded FPCBs to function as robotic mechanisms rather than simply as passive electronics substrates.

Salps are underwater invertebrates considered to be among the world’s most energy-efficient examples of jet propulsion. They can swim as solitary individuals or as physically connected colonies, coordinating their jets to produce collective movement. Inspired by salps, we developed the SALP (Salp-inspired Approach to Low-energy Propulsion) system, where individual SALP robots can be physically connected into a multi-SALP group, and we investigate the coupled effects of physical arrangement and jet coordination on the swimming performance and energy efficiency of a two-SALP system. We conduct free swimming tests to evaluate locomotion performance metrics and find that the two-SALP system, when properly coordinated, is able to swim with 15.7% higher speed and 11.3% lower cost of transport than the single SALP. Supporting flow characterization experiments using particle image velocimetry reveal vortex ring structures emanating from robot SALP nozzles. The data suggest that propulsion performance is affected by the spatial arrangement of the vortex ring structure. In particular, we find that SALP systems that produce a parallel vortex ring arrangement produce less vortex circulation and impulse than an in-series vortex ring arrangement. Overall, the SALP system is a useful platform for exploring salp-inspired multi-jet locomotion strategies, enabling decoupling of physical and control parameters to expose underlying locomotion physics in ways that are difficult with the biological salp. These insights advance our understanding of multi-jet locomotion and support the development of more energy-efficient jet-propelled underwater robots in the future.

This paper addresses the Dubins path planning problem for vehicles in 3D space. In particular, we consider the problem of computing CSC paths -- paths that consist of a circular arc (C) followed by a straight segment (S) followed by a circular arc (C). These paths are useful for vehicles such as fixed-wing aircraft and underwater submersibles that are subject to lower bounds on turn radius. We present a new parameterization that reduces the 3D CSC planning problem to a search over 2 variables, thus lowering search complexity, while also providing gradients that assist that search. We use these equations with a numerical solver to explore numbers and types of solutions computed for a variety of planar and 3D scenarios. Our method successfully computes CSC paths for the large majority of test cases, indicating that it could be useful for future generation of robust, efficient curvature-constrained trajectories.

Aerial vehicle missions require navigating trade-offs during design, such as the range, speed, maneuverability, and size. Multi-modal aerial vehicles enable this trade-off to be negotiated during flight. This paper presents a Bistable Aerial Transformer (BAT) robot, a novel morphing hybrid aerial vehicle that switches between quadrotor and fixed-wing modes via rapid acceleration and without any additional actuation beyond those required for normal flight. The design features a compliant bistable mechanism made of thermoplastic polyurethane (TPU) that bears a large mass at the center of the robot’s body. When accelerating, inertial forces transition the vehicle between its stable modes, and a four-bar linkage connected to the bistable mechanism folds the vehicle’s wings in and out. The paper includes the full robot design and a comparison of the fabricated system to the elastodynamic simulation. Successful transitions between the two modes in mid-flight, as well as sustained flight in each mode indicate that the vehicle experiences higher agility in the quadrotor mode and higher flight efficiency in the fixed-wing mode, at an energy equivalent cost of only 2 s of flight time per pair of transitions. The vehicle demonstrates how compliant and bistable mechanisms can be integrated into future aerial vehicles for controllable self-reconfiguration for tasks such as surveillance and sampling that require a combination of maneuverability and long-distance flight.

While there has been much work in the space of embodied intelligence, we as a field have struggled to define what exactly embodied intelligence is and how it should be used. In this paper, we propose that there are multiple types of embodied intelligence, and that these different types of embodied intelligence are suited to different types of tasks. We introduce a method for classifying tasks according to their objective and occurrence, and we describe how existing work in embodied intelligence fits into this framework. We hope that this proposed framework will initiate a discussion to more formally think about the role that embodied intelligence plays and the value that it brings to engineering and robotics.

Origami processes can generate both rigid and compliant structures from the same homogeneous sheet material. In this article, we advance the origami robotics literature by showing that it is possible to construct an arbitrary rigid kinematic chain with prescribed joint compliance from a single tubular sheet. Our “Kinegami” algorithm converts a Denavit–Hartenberg specification into a single-sheet crease pattern for an equivalent serial robot mechanism by composing origami modules from a catalogue. The algorithm arises from the key observation that tubular origami linkage design reduces to a Dubins path planning problem. The automatically generated structural connections and movable joints that realize the specified design can also be endowed with independent user-specified compliance. We apply the Kinegami algorithm to a number of common robot mechanisms and hand-fold their algorithmically generated single-sheet crease patterns into functioning kinematic chains. We believe this is the first completely automated end-to-end system for converting an abstract manipulator specification into a physically realizable origami design that requires no additional human input.

Self-folding systems, which can transform autonomously from a flat sheet into a 3D machine, provide opportunities for rapidly fabricable robots that are deployable on-demand. Existing self-folding fabrication processes convert fold patterns into laminated structures that respond to external stimuli, most commonly heat. However, demonstrations of these approaches have been generally limited to simple fold patterns with little ambiguity in folding configuration, and the reliability of self-folding drops drastically with the fold pattern complexity. In this paper, we explore methods of biasing a symmetric fold pattern, the origami hyperbolic paraboloid (hypar), to fold into one of the two possible configurations. The biasing methods are simulated using a bar-and-hinge inspired self-folding model that defines a single fold as a bending beam and the hypar crease pattern as an elastic spring network. Simulation results are also verified on physical samples. Based on these results, three techniques to bias the hypar by manipulating the target fold angles are proposed and tested. The results show that biasing a self-folding pattern can increase folding accuracy from 50% (purely random) to 70% and provide insights for improving the reliability of future self-folding systems with complex fold patterns.