Alle Publikationen
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2016
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(2016) : Mobile robot navigation for human-robot social interaction: 2016 16th International Conference on Control, Automation and Systems (ICCAS): Gyeongju, Korea: IEEE, S. 1298-1303
DOI: https://doi.org/10.1109/ICCAS.2016.7832481 Abstract: Human social interactions are believed to be described by a mathematical model called the Social Force Model (SFM). A variety of mobile robot research has often used the SFM to generate an appropriate navigation behavior. However, to create a mobile robot that moves around in a human-populated environment in a socially acceptable way, it should be stressed that the social conventions are strictly obeyed. This paper proposes an extended SFM between humans and robots, called the Social Relationship Model (SRM), to enable mobile robots to generate navigation paths in a human-like manner. Simulation results show notable advantages of SRM over the Transition based Rapidly Random Tree (T-RRT) path planning algorithm. The proposed method ensures a socially acceptable robot path, one of the most important issues for human-robot symbiosis.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, Force, human-populated environment, human-robot interaction, human-robot social interaction, Human-Robot Symbiosis, ieee xplore, Mathematical model, mobile robot navigation, Mobile robots, Navigation, path planning, service robot, SFM, social force model, social relationship model, SRM, Symbiosis, transition based rapidly random tree, trees (mathematics), T-RRT path planning algorithm 2014
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(2014): Learning Compliant Manipulation through Kinesthetic and Tactile Human-Robot Interaction. In: IEEE Transactions on Haptics 7 (3), S. 367-380. DOI: 10.1109/TOH.2013.54
DOI: https://doi.org/10.1109/TOH.2013.54 Abstract: Robot Learning from Demonstration (RLfD) has been identified as a key element for making robots useful in daily lives. A wide range of techniques has been proposed for deriving a task model from a set of demonstrations of the task. Most previous works use learning to model the kinematics of the task, and for autonomous execution the robot then relies on a stiff position controller. While many tasks can and have been learned this way, there are tasks in which controlling the position alone is insufficient to achieve the goals of the task. These are typically tasks that involve contact or require a specific response to physical perturbations. The question of how to adjust the compliance to suit the need of the task has not yet been fully treated in Robot Learning from Demonstration. In this paper, we address this issue and present interfaces that allow a human teacher to indicate compliance variations by physically interacting with the robot during task execution. We validate our approach in two different experiments on the 7 DoF Barrett WAM and KUKA LWR robot manipulators. Furthermore, we conduct a user study to evaluate the usability of our approach from a non-roboticists perspective.
Keywords: Algorithms, Analysis, Bedienung & Handhabung, Biomechanical Phenomena, compliance control, compliance variations, compliant control, compliant manipulation, Computer Simulation, education, Force, haptic feedback, haptic interfaces, human-robot interaction, Humans, Impedance, Joints, Kinesthesis, kinesthetic human-robot interaction, KUKA LWR robot manipulators, Learning, manipulator kinematics, Physical Human-Robot Interaction, position control, RLfD, Robot kinematics, robot learning from demonstration, Robot sensing systems, Robotics, stiff position controller, tactile human-robot interaction, tactile interfaces, task kinematics, task model, Task Performance, Touch 2010
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(2010) : Secondary action in robot motion: 19th International Symposium in Robot and Human Interactive Communication: Viareggio, Italy: IEEE, S. 310-315
DOI: https://doi.org/10.1109/ROMAN.2010.5598730 Abstract: Secondary action, a concept borrowed from character animation, improves the animation realism by augmenting natural, passive motion to primary action. We use dynamic simulation to induce three techniques of secondary motion for robot hardware, which exploit actuation passivity to overcome hardware constraints and change the dynamic perception of the robot and its motion characteristics. Results of secondary motion due to internal and external forces are presented including discussion on how to choose the appropriate technique for a particular application.
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(2010) : Smooth collision avoidance in human-robot coexisting environment: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems: Taipei, Taiwan: IEEE, S. 3887-3892
DOI: https://doi.org/10.1109/IROS.2010.5649673 Abstract: In order for service robots to safely coexist with humans, collision avoidance with humans is the most important issue. On the other hand, working efficiencies are also important and cannot be ignored. In this paper, we propose a method to estimate a pedestrian’s behavior. Based on the estimation, we realize smooth collision avoidances between a robot and a human. A robot detects pedestrians by using a laser range finder and tracks them by a Kalman filter. We apply the social force model to the observed trajectory for a determination whether the pedestrian intends to avoid a collision with the robot or not. The robot selects an appropriate behavior based on the estimation results. We conducted experiments that a robot and a person pass each other. Through the experiments, the usefulness of the proposed method was demonstrated.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, Force, human-robot coexisting environment, human-robot interaction, ieee xplore, Kalman filter, Kalman filters, laser range finder, laser ranging, Leg, Mobile robots, pedestrian behavior, Robot kinematics, service robot, smooth collision avoidance, Trajectory
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