When academic researchers develop and validate autonomous driving algorithms, there is a challenge in balancing high-performance capabilities with the cost and complexity of the vehicle platform. Much of today’s research on autonomous vehicles (AV) is limited to experimentation on expensive commercial vehicles that require large skilled teams to retrofit the vehicles and test them in dedicated facilities. On the other hand, 1/10th-1/16th scaled-down vehicle platforms are more affordable but have limited similitude in performance and drivability. To address this issue, we present the design of a one-third-scale autonomous electric go-kart platform with open-source mechatronics design along with fully functional autonomous driving software. The platform’s multi-modal driving system is capable of manual, autonomous, and teleoperation driving modes. It also features a flexible sensing suite for the algorithm deployment across perception, localization, planning, and control. This development serves as a bridge between full-scale vehicles and reduced-scale cars while accelerating cost-effective algorithmic advancements. Our experimental results demonstrate the AV4EV platform’s capabilities and ease of use for developing new AV algorithms. All materials are available at AV4EV.org to stimulate collaborative efforts within the AV and electric vehicle (EV) communities.

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.