Abstract: Traditional manual wheelchairs have a fixed seat with no movement or angle adjustment, which can seriously affect the user’s comfort and greatly limit user experience. However, the electric wheelchair relies on strong intelligence and automatic features; it can not only realize the multidegree freedom adjustment of the human body and the seat but also has a rich and powerful man–machine control interface, which greatly facilitates and improves the user experience.
Abstract: The feature pyramid, which is a vital component of the convolutional neural networks, plays a significant role in several perception tasks, including object detection for autonomous driving. However, how to better fuse multi-level and multi-sensor feature pyramids is still a significant challenge, especially for object detection.
Abstract: Human-made concrete structures require cutting-edge inspection tools to ensure the quality of the construction to meet the applicable building codes and to maintain the sustainability of the aging infrastructure. This paper introduces a wall-climbing robot for metric concrete inspection that can reach difficult-to-access locations with a close-up view for visual data collection and real-time flaws detection and localization.
Abstract: Current learning-based 3-D object detection accuracy is heavily impacted by the annotation quality. It is still a challenge to expect an overall high detection accuracy for all classes under different scenarios given the dataset sparsity.
Abstract: This paper proposes a real-time multi-scale semantic segmentation network (MsNet). MsNet is a combination of our novel multi-scale fusion with matching attention model (MFMA) as the decoding network and the network searched by asymptotic neural architecture search (ANAS) or MobileNetV3 as the encoding network.
Abstract: Autonomous wheelchairs can address a very large need in many populations by serving as the gateway to a much higher degree of independence and mobility capability. This is due to the fact that the big picture idea for autonomous wheelchairs integration into the transportation chain is to allow for individuals to be able to utilize the Intelligent wheelchair to reach the vehicle (regardless of terrain), mount into autonomous wheelchair that navigates to desired destination, and finally autonomous wheelchair dismounts.
Abstract: The fundamental aspect of unmanned ground vehicle (UGV) navigation, especially over off-road environments, are representations of terrain describing geometry, types, and traversability. One of the typical representations of the environment is digital surface models (DSMs) which efficiently encode geometric information.
Abstract: With the particular passage capability, all-terrain vehicle (ATV) has been widely used for off-road scenarios. In this research, we conduct a lateral sway stability analysis for the suspension mechanism of a general vehicle and establish a mathematical model of static and dynamic stability based on the maximum lateral sway angle and lateral sway acceleration, by considering the combined angular stiffness of independent suspension, angular stiffness of the lateral stabilizer bar and vertical stiffness of tires.
Abstract: The concrete aging problem has gained more attention in recent years as more bridges and tunnels in the United States lack proper maintenance. Though the Federal Highway Administration requires these public concrete structures to be inspected regularly, on-site manual inspection by human operators is time-consuming and labor-intensive.
Abstract: Handicapped individuals often rely heavily on various assistive technologies including wheelchairs and the purpose of these technologies is to enable greater levels of independence for the user. In the development of autonomous wheelchairs, it is imperative that the wheelchair maintains appropriate stability for the user in an outdoor urban environment.