Innovative Safety Measures for Human-Robot Interaction in Dynamic Environment Using RRT and IR Sensing

Abstract

This study addresses the critical challenge by developing reliable safety protocols for robots in domestic environments, introducing an advanced safety algorithm leveraging dynamic path planning and real-time obstacle avoidance strategies. Motivated by the gap in research focusing on domestic HRI as opposed to industrial contexts, this study utilizes a 7-degree of freedom (DOF) Kinova Gen3 arm robot model in simulated settings. The methodology is evaluated against ISO/TS 15066:2016 protocols, demonstrating its efficacy and adaptability in real-world scenarios. The open-source 3D robotics simulator Gazebo is employed to run the simulations, incorporating safety protocols to control the robot's arm velocity and trajectory, minimizing the risk of collision and auto-correcting the trajectory in the presence of obstacles. An IR distance sensor is embedded in the virtual robot to measure distance data, including range and field of view. In the simulation, a human is defined as a ‘virtual obstacle,’ and the robot uses the IR distance sensor to measure the distance to the human through infrared light. The Open Motion Planning Library (OMPL) uses the Rapidly Exploring Random Tree (RRT) algorithm for motion planning, selecting random configurations while respecting the robot's kinematic constraints. The robot interprets sensor readings to determine the distance to nearby humans and adjusts its speed accordingly. The robot stops moving to avoid collision when the distance falls below a determined threshold. The simulation results provide valuable insights into the features necessary to adapt this HRI system to real-life domestic environments, evaluating the safety region for HRI within a range from -0.1m to 0.1m. The significance of this study lies in its focus on domestic environments, an area that has been relatively underexplored compared to industrial settings. By addressing the complexities and unpredictability of home environments, this research aims to enhance the integration of robots into everyday domestic settings, promoting safer and more effective human-robot interactions. The findings underscore the importance of dynamic safety measures and real-time adaptability, contributing to the advancement of safer HRI protocols in domestic environments.