Minimum distance calculation using laser scanner and IMUs for safe human-robot interaction

Abstract In this study we investigate the use of a laser scanner/range-finder and inertial measurement units (IMUs) for the application of human-robot interaction in a dynamic environment with moving obstacles/humans. Humans and robots are represented by capsules, allowing to calculate the human-robot minimum distance on-the-fly. A major challenge is to capture the capsules pose. Data from a laser scanner and IMUs attached to the human body are fused to define the torso relative position and the upper body (arms and chest) configuration, respectively. Collision avoidance is achieved with a customized potential field’s method that allows to adjust the pre-defined robot paths established off-line while keeping the task target. The proposed framework is validated in real environment using a SICK laser scanner, IMUs and a KUKA iiwa robot. Experiments demonstrated the robustness of the proposed approach in capturing human motion, calculating the human-robot minimum distance and the robot behavior that smoothly avoids collisions with the human.

[1]  Nuno Mendes,et al.  Kalman filter-based yaw angle estimation by fusing inertial and magnetic sensing: a case study using low cost sensors , 2015 .

[2]  Tie Zhang,et al.  Virtual Velocity Vector-Based Offline Collision-Free Path Planning of Industrial Robotic Manipulator , 2015 .

[3]  Oussama Khatib,et al.  A depth space approach to human-robot collision avoidance , 2012, 2012 IEEE International Conference on Robotics and Automation.

[4]  Lihui Wang,et al.  Depth camera based collision avoidance via active robot control , 2014 .

[5]  Yoshihiko Nakamura,et al.  Inverse kinematic solutions with singularity robustness for robot manipulator control , 1986 .

[6]  Kai Oliver Arras,et al.  Tracking people in 3D using a bottom-up top-down detector , 2011, 2011 IEEE International Conference on Robotics and Automation.

[7]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[8]  Rui Wang,et al.  Research Methods for Human Activity Space Based on Vicon Motion Capture System , 2017, 2017 5th International Conference on Enterprise Systems (ES).

[9]  Wolfram Burgard,et al.  Accurate human motion capture in large areas by combining IMU- and laser-based people tracking , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Woojin Chung,et al.  Localization of a Mobile Robot Using a Laser Range Finder in a Glass-Walled Environment , 2016, IEEE Transactions on Industrial Electronics.

[11]  Lorenzo Molinari Tosatti,et al.  Trajectory-dependent safe distances in human-robot interaction , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[12]  Nikolaos G. Tsagarakis,et al.  Efficient self-collision avoidance based on focus of interest for humanoid robots , 2015, 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids).

[13]  Rajnikant V. Patel,et al.  Control of Redundant Robot Manipulators: Theory and Experiments , 2005 .

[14]  Yasumichi Aiyama,et al.  On-line collision detection of n-robot industrial manipulators using advanced collision map , 2015, 2015 International Conference on Advanced Robotics (ICAR).

[15]  Paul Bosscher,et al.  Real-time collision avoidance algorithm for robotic manipulators , 2009, 2009 IEEE International Conference on Technologies for Practical Robot Applications.

[16]  Geir Hovland,et al.  Collision avoidance with potential fields based on parallel processing of 3D-point cloud data on the GPU , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[17]  Olivier Gibaru,et al.  Survey of methods for design of collaborative robotics applications- Why safety is a barrier to more widespread robotics uptake , 2018, ICMRE.

[18]  Jeremy A Marvel,et al.  Implementing Speed and Separation Monitoring in Collaborative Robot Workcells. , 2017, Robotics and computer-integrated manufacturing.

[19]  Sungsoo Rhim,et al.  Allowable Maximum Safe Velocity Control based on Human-Robot Distance for Collaborative Robot , 2018, 2018 15th International Conference on Ubiquitous Robots (UR).

[20]  Darius Burschka,et al.  Real-time reactive motion generation based on variable attractor dynamics and shaped velocities , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[21]  Byung-Ju Yi,et al.  Development of a Laser-Range-Finder-Based Human Tracking and Control Algorithm for a Marathoner Service Robot , 2014, IEEE/ASME Transactions on Mechatronics.

[22]  Pedro Neto,et al.  KUKA Sunrise Toolbox: Interfacing Collaborative Robots With MATLAB , 2019, IEEE Robotics & Automation Magazine.

[23]  Gheorghe Leonte Mogan,et al.  Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning , 2012 .

[24]  Meng Chen,et al.  Dynamic obstacle avoidance for manipulators using distance calculation and discrete detection , 2018 .

[25]  Ivan Lundberg,et al.  Safety of collaborative industrial robots: Certification possibilities for a collaborative assembly robot concept , 2011, 2011 IEEE International Symposium on Assembly and Manufacturing (ISAM).

[26]  Pedro Neto,et al.  Efficient Calculation of Minimum Distance Between Capsules and Its Use in Robotics , 2019, IEEE Access.

[27]  Vittorio Rampa,et al.  Safe human-robot cooperation through sensor-less radio localization , 2014, 2014 12th IEEE International Conference on Industrial Informatics (INDIN).

[28]  Karl Johan Åström,et al.  PID Controllers: Theory, Design, and Tuning , 1995 .

[29]  Nuno Mendes,et al.  Minimum Distance Calculation for Safe Human Robot Interaction , 2017 .

[30]  D. Roetenberg,et al.  Xsens MVN: Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors , 2009 .

[31]  Oussama Khatib,et al.  Control of Redundant Robots Under Hard Joint Constraints: Saturation in the Null Space , 2015, IEEE Transactions on Robotics.

[32]  Lihui Wang,et al.  Active collision avoidance for human–robot collaboration driven by vision sensors , 2017, Int. J. Comput. Integr. Manuf..

[33]  Stefan Schaal,et al.  Movement reproduction and obstacle avoidance with dynamic movement primitives and potential fields , 2008, Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots.

[34]  Yasumichi Aiyama,et al.  Collision avoidance of two manipulators using RT-Middleware , 2011, 2011 IEEE/SICE International Symposium on System Integration (SII).

[35]  S. G. Ponnambalam,et al.  Obstacle avoidance control of redundant robots using variants of particle swarm optimization , 2012 .

[36]  Yasumichi Aiyama,et al.  On-line collision avoidance between two robot manipulators using collision map and simple Escaping method , 2013, Proceedings of the 2013 IEEE/SICE International Symposium on System Integration.

[37]  Eduardo Rocon,et al.  Global Kalman filter approaches to estimate absolute angles of lower limb segments , 2017, Biomedical engineering online.