Uploaded May 2018 | Updated September 2026, 2 weeks ago
ICRA 2018 Spotlight Video
Interactive Session Wed PM Pod K.6
Authors: Tsiami, Antigoni; Koutras, Petros; Efthymiou, Niki; Filntisis, Panagiotis Paraskevas; Potamianos, Gerasimos; Maragos, Petros
Title: Multi3: Multi-Sensory Perception System for Multi-Modal Child Interaction with Multiple Robots
Abstract:
Child-robot interaction is an interdisciplinary research area that has been attracting growing interest, primarily focusing on edutainment applications. A crucial factor to the successful deployment and wide adoption of such applications remains the robust perception of the child's multi-modal actions, when interacting with the robot in a natural and untethered fashion. Since robotic sensory and perception capabilities are platform-dependent and most often rather limited, we propose a multiple Kinect-based system to perceive the child-robot interaction scene that is robot-independent and suitable for indoors interaction scenarios. The audio-visual input from the Kinect sensors is fed into speech, gesture, and action recognition modules, appropriately developed in this paper to address the challenging nature of child-robot interaction. For this purpose, data from multiple children are collected and used for module training or adaptation. Further, information from the multiple sensors is fused to enhance module performance. The perception system is integrated in a modular multi-robot architecture demonstrating its flexibility and scalability with different robotic platforms. The whole system, called Multi3, is evaluated, both objectively at the module level and subjectively in its entirety, under appropriate child-robot interaction scenarios containing several carefully designed games between children and robots.
ICRA 2018 Spotlight Video
Interactive Session Wed PM Pod K.6
Authors: Tsiami, Antigoni; Koutras, Petros; Efthymiou, Niki; Filntisis, Panagiotis Paraskevas; Potamianos, Gerasimos; Maragos, Petros
Title: Multi3: Multi-Sensory Perception System for Multi-Modal Child Interaction with Multiple Robots
Abstract:
Child-robot interaction is an interdisciplinary research area that has been attracting growing interest, primarily focusing on edutainment applications. A crucial factor to the successful deployment and wide adoption of such applications remains the robust perception of the child's multi-modal actions, when interacting with the robot in a natural and untethered fashion. Since robotic sensory and perception capabilities are platform-dependent and most often rather limited, we propose a multiple Kinect-based system to perceive the child-robot interaction scene that is robot-independent and suitable for indoors interaction scenarios. The audio-visual input from the Kinect sensors is fed into speech, gesture, and action recognition modules, appropriately developed in this paper to address the challenging nature of child-robot interaction. For this purpose, data from multiple children are collected and used for module training or adaptation. Further, information from the multiple sensors is fused to enhance module performance. The perception system is integrated in a modular multi-robot architecture demonstrating its flexibility and scalability with different robotic platforms. The whole system, called Multi3, is evaluated, both objectively at the module level and subjectively in its entirety, under appropriate child-robot interaction scenarios containing several carefully designed games between children and robots.



![On Bisection Continuous Collision Checking Method: Spherical Joints and Minimum Distance to Obstacle
ICRA 2018 Spotlight Video
Interactive Session Thu PM Pod R.3
Authors: TARBOURIECH, Sonny; Suleiman, Wael
Title: On Bisection Continuous Collision Checking Method: Spherical Joints and Minimum Distance to Obstacles
Abstract:
In this paper, we adapt the Continuous Collision Checking Detection (CCD) method proposed in [1] to efficiently handle the case of spherical and two revolute joints, this kind of joints is very common in modern robotic systems. The new formulations provide more tight motion bounds, thus increase the success rate of checking collision-free paths. We also propose an extension to get the minimum distance to obstacles along a path, this information is primordial as it allows sampling-based motion planning techniques to sort collision-free paths according to their minimum clearance. We have integrated our implementation into a sampling-based motion planning technique and validated it through simulation and on the real Baxter research robot. The experiments revealed that the method not only does not miss any collision between the robot and the obstacles, but also the minimum distance extension provides the path with the maximum clearance at no additional computational cost. On Bisection Continuous Collision Checking Method: Spherical Joints and Minimum Distance to Obstacle](https://i.ytimg.com/vi/XYwj53x-35E/mqdefault.jpg)






