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

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.

Innocence over utilitarianism - Heightened Moral Standards for Robots in Rescue Dilemmas PREPRINT

With rapid developments in robotics and artificial intelligence, the prospect of automating rescue operations and protecting trained professionals from life-threatening risk is becoming increasingly viable. What moral standards do people expect rescue robots to enforce? Previous research has emphasized the notion that robots are expected to conform to specifically utilitarian standards. In a series of seven experiments (total N = 3752) and one public survey (N = ~19 000), we compared people’s evaluations of human and robotic rescue agents in the context of boating accidents, while manipulating the victims’ negligence. Relative to human lifeguards, robots of various kinds are expected to save innocent lives, even when doing so entails sacrificing a larger number of negligent individuals (Studies 1-2b). This finding was replicated in a large-scale web survey (Study 3) and was found to reverse when matching the victims in their degree of negligence (Study 5). In sum, robots are not merely expected to be more utilitarian, but rather are held to higher moral standards altogether.

ResQbot 2.0: An Improved Design of a Mobile Rescue Robot with an Inflatable Neck Securing Device for Safe Casualty Extraction

Despite the fact that a large number of research studies have been conducted in the field of search and rescue robotics, significantly little attention has been given to the development of rescue robots capable of performing physical rescue interventions, including loading and transporting victims to a safe zone—i.e., casualty extraction tasks. The aim of this study is to develop a mobile rescue robot that could assist first responders when saving casualties from a dangerous area by performing a casualty extraction procedure whilst ensuring that no additional injury is caused by the operation and no additional lives are put at risk. In this paper, we present a novel design of ResQbot 2.0—a mobile rescue robot designed for performing the casualty extraction task. This robot is a stretcher-type casualty extraction robot, which is a significantly improved version of the initial proof-of-concept prototype, ResQbot (retrospectively referred to as ResQbot 1.0), that has been developed in our previous work. The proposed designs and development of the mechanical system of ResQbot 2.0, as well as the method for safely loading a full-body casualty onto the robot’s ‘stretcher bed’, are described in detail based on the conducted literature review, evaluation of our previous work, and feedback provided by medical professionals. We perform simulation experiments in the Gazebo physics engine simulator to verify the proposed design and the casualty extraction procedure. The simulation results demonstrate the capability of ResQbot 2.0 to carry out safe casualty extractions successfully.