Staircase Detection, Characterization and Approach Pipeline for Search and Rescue Robots

Abstract

Currently, most rescue robots are mainly teleoperated and integrate some level of autonomy to reduce the operator’s workload, allowing them to focus on the primary mission tasks. One of the main causes of mission failure are human errors and increasing the robot’s autonomy can increase the probability of success. For this reason, in this work, a stair detection and characterization pipeline is presented. The pipeline is tested on a differential drive robot using the ROS middleware, YOLOv4-tiny and a region growing based clustering algorithm. The pipeline’s staircase detector was implemented using the Neural Compute Engines (NCEs) of the OpenCV AI Kit with Depth (OAK-D) RGB-D camera, which allowed the implementation using the robot’s computer without a GPU and, thus, could be implemented in similar robots to increase autonomy. Furthermore, by using this pipeline we were able to implement a Fuzzy controller that allows the robot to align itself, autonomously, with the staircase. Our work can be used in different robots running the ROS middleware and can increase autonomy, allowing the operator to focus on the primary mission tasks. Furthermore, due to the design of the pipeline, it can be used with different types of RGB-D cameras, including those that generate noisy point clouds from low disparity depth images.

New Trends in the Control of Robots and Mechatronic Systems

“…Additionally, the control of ground vehicles is discussed in this Special Issue in [19,20]. In [19], a stair detection and characterization pipeline is presented.…”

“…Additionally, the control of ground vehicles is discussed in this Special Issue in [19,20]. In [19], a stair detection and characterization pipeline is presented. The pipeline is tested on a differential drive robot using the ROS middleware.…”

Terrain-aware semantic mapping for cooperative subterranean exploration

“… Harms et al (2015) presents an approach to stair detection which utilized a stereo-vision camera system and a convolutional kernel to extract the alternating concave and convex edges of the steps of a stairway. Sánchez-Rojas et al (2021) presents a hybrid visual and geometric approach to stair detection as well as a fuzzy logic controller for the alignment of robots to the detected stairway. ( Westfechtel et al, 2016 , Westfechtel et al, 2018 ) introduces StairwayDetection, an open-source package that directly classifies the various parts of stairways using a graph-based approach, including the stair tread, riser, and railing segments.…”