The omni-directional kart, named “OK-1”, is a hybrid electric vehicle with technology of omni-directional steering, which is designed and developed in the Advance Robotics Lab. It is omni-directional, because it can make crab-like parallel translation and tornado-like rotation. Hence, parking becomes an easy manipulation for even a freshman of driving.Omni-directional steering technology consists of 4 wheel independent drive-by-wire technology and 4 wheel independent steer-by-wire technology. For every steer-drive module, there is one steering motor and one driving motor. The four modules can be configured into various steering modes, for instances front wheel steering, four wheel steering, zero-radius turning, lateral parking, etc. The vehicle mobility is significantly enhanced, and consequently, parking in tight regions becomes a piece of cake. Meanwhile, the canceling of traditional transition and steering mechanism makes the mass center of the vehicle lower, and thus the vehicle is more stable.With the capability of zero-radius turning (ZRT), rotation of the vehicle can be independent on translation. Thus the occupied area is minimized, and there is almost no turn which can not be made by OK-1. For laterally arranged parking slots, ZRT mode can help to park the vehicle easily.With the mode of lateral parking (LP), lateral translation is independent on rotation of the vehicle. In the occasion that the vehicle is restricted by a front vehicle and a rear one, it can still move in or our freely.

The objective of the development of Treebot is to assist or replace human being in performing forestry tasks on trees. Treebot is composed of a pair of tree grippers that permits Treebot to attach on a wide variety of trees with a wide range of gripping curvature, and a novel continuum maneuvering structure that permits Treebot has high maneuverability and adaptability. In the robot actuation, merely five actuators are necessary. Although Treebot weighs 600grams only, it has payload capability of 1.75kg which is nearly three times of its own weight.A certain level of autonomous climbing ability of Treebot is helpful to reduce the complexity of manipulation by users. An autonomous climbing strategy for Treebot is thus proposed. To determine the motions to climb up autonomously in an unknown environment, a robot must be equipped with sensors that can explore the environment. Vision-based sensors provide rich information about the environment. However, they require a great deal of computational power. Moreover, light conditions vary in outdoor environments, which may affect the accuracy of visual information. There are many living creatures that do not rely on visual information, but can navigate well in their natural environment. Inchworms, for example, navigate on trees by using only their sense of touch. Although the information obtained by tactile sensors is not rich, it is reliable. Furthermore, the processing of tactile information is much simpler than that of visual information. The development of the algorithm can also reveal how tactile sensors can best be employed in autonomous tree climbing.Inspired by arboreal animals, an algorithm is developed to allow Treebot to climb irregularly shaped trees autonomously by using tactile sensors and a tilting sensor only. The development of the algorithm can also reveal how tactile sensors can best be employed in autonomous tree climbing.