During a natural disaster such as hurricane, earthquake, or fire, robots have the potential to explore vast areas and provide valuable aid in search & rescue efforts. These scenarios are often high-pressure and time-critical with dynamically-changing task goals. One limitation to these large scale deployments is effective human-robot interaction. Prior work shows that collaboration between one human and one robot benefits from shared control. Here we evaluate the efficacy of shared control for human-swarm teaming in an immersive virtual reality environment. Although there are many human-swarm interaction paradigms, few are evaluated in high-pressure settings representative of their intended end use. We have developed an open-source virtual reality testbed for realistic evaluation of human-swarm teaming performance under pressure. We conduct a user study ($\mathrm{n}=16$) comparing four human-swarm paradigms to a baseline condition with no robotic assistance. Shared control significantly reduces the number of instructions needed to operate the robots. While shared control leads to marginally improved team performance in experienced participants, novices perform best when the robots are fully autonomous. Our experimental results suggest that in immersive, high-pressure settings, the benefits of robotic assistance may depend on how the human and robots interact, and the human operator's expertise.

Origami robots are well-suited for jumping maneuvers because of their light weight and ability to incorporate actuation and control strategies directly into the robot body. However, existing origami robots often model fold patterns as rigidly foldable and fail to take advantage of deformation in an origami sheet for potential energy storage. In this paper, we consider a parametric origami tessellation, the Reconfigurable Expanding Bistable Origami (REBO) pattern, which leverages face deformations to act as a nonlinear spring. We present a pseudo-rigid-body model for the REBO for computing its energy stored when compressed to a given displacement and compare that model to experimental measurements taken on a mechanical testing system. This stored potential energy, when released quickly, can cause the pattern to jump. Using our model and experimental data, we design and fabricate a jumping robot, REBOund, that uses the spring-like REBO pattern as its body. Four lightweight servo motors with custom release mechanisms allow for quick compression and release of the origami pattern, allowing the fold pattern to jump over its own height even when carrying 5 times its own weight in electronics and power. We further demonstrate that small geometric changes to the pattern allow us to change the jump height without changing the actuation or control mechanism.