Step modeling and safe path planning for a lower limb exoskeleton The walking experience in environments with obstacles is a challenge for patients with lower limb pathology. A transparent exoskeleton is an interesting solution since it guarantees the performance of autonomous motion. In this paper, we present a new method to detect and model steps using point cloud data to find a feasible path for the exoskeleton to perform. We use a RGBD sensor to obtain depth information and perform a scene segmentation strategy. Next, we classify the different detected elements either as a floor, step or obstacle and then use a path planning method to find a collisionfree path. Experiments show that the system accomplished satisfactory results for the presented scenarios.

Stairs Reconstruction with 3D Point Cloud for Gait Generation of Lower Limb Exoskeleton Robot With the aging of the population, a considerable number of elderly persons suffer from walking disability. Lower limb exoskeleton robots have been proved to be effective in rehabilitation training and walking assistance. Though significant advancement has been made in the last decade, lacking the ability of adapting to complex terrain is one of the main challenges that restrict the wide application of exoskeleton robots. Thus we focus on the environmental perception and corresponding gait pattern generation of lower limb assistant exoskeleton. In this paper, we introduce a method to generate gait of exoskeleton walking on a stair, which applies the L0 minimizationbased acquisition and reconstruction of stairs information through 3D Point Cloud. The results of experiments show that our method can precisely measure the physical dimension information of stairs.