Mobile robots are increasingly being deployed in public spaces such as shopping malls, airports, and urban sidewalks. Most of these robots are designed with human-aware motion planning capabilities but are not designed to communicate with pedestrians. Pedestrians encounter these robots without prior understanding of the robots' behaviour, which can cause discomfort, confusion, and delayed social acceptance. In this research, we explore the common human-robot interaction at a doorway or bottleneck in a structured environment. We designed and evaluated communication cues used by a robot when yielding to a pedestrian in this scenario. We conducted an online user study with 102 participants using videos of a set of robot-to-human yielding cues. Results show that a Robot Retreating cue was the most socially acceptable cue. The results of this work help guide the development of mobile robots for public spaces.
University of British Columbia（不列颠哥伦比亚大学）；Monash University（莫纳什大学）
Mobile robots have recently been deployed in public spaces such as shopping malls, airports, and urban sidewalks. Most of these robots are designed with human-aware motion planning capabilities but are not designed to communicate with pedestrians. Pedestrians that encounter these robots without prior understanding of the robots' behaviour can experience discomfort, confusion, and delayed social acceptance. In this work we designed and evaluated nonverbal robot motion legibility cues, which communicate a mobile robot's motion intention to pedestrians. We compared a motion legibility cue using P…
In this paper, we present an algorithm to efficiently learn socially-compliant navigation policies from observations of human trajectories. As mobile robots come to inhabit and traffic social spaces, they must account for social cues and behave in a socially compliant manner. We focus on learning such cues from examples. We describe an inverse reinforcement learning based algorithm which learns from human trajectory observations without knowing their specific actions. We increase the sample-efficiency of our approach over alternative methods by leveraging the notion of a replay buffer (found i…
This paper presents a method of computing free motions of a planar assembly of rigid bodies connected by loose joints. Joints are modeled using local distance constraints, which are then linearized with respect to configuration space velocities, yielding a linear programming formulation that allows analysis of systems with thousands of rigid bodies. Potential applications include analysis of collections of modular robots, structural stability perturbation analysis, tolerance analysis for mechanical systems, and formation control of mobile robots.
Université Laval（拉瓦尔大学）；Centre de Recherche Industrielle du Québec（魁北克工业研究中心）
Forestry is a major industry in many parts of the world. It relies on forest inventory, which consists of measuring tree attributes. We propose to use 3D mapping, based on the iterative closest point algorithm, to automatically measure tree diameters in forests from mobile robot observations. While previous studies showed the potential for such technology, they lacked a rigorous analysis of diameter estimation methods in challenging forest environments. Here, we validated multiple diameter estimation methods, including two novel ones, in a new varied dataset of four different forest sites, 11 …
This paper describes a system whereby a robot detects and track human-meaningful navigational cues as it navigates in an indoor environment. It is intended as the sensor front-end for a mobile robot system that can communicate its navigational context with human users. From simulated LiDAR scan data we construct a set of 2D occupancy grid bitmaps, then hand-label these with human-scale navigational features such as closed doors, open corridors and intersections. We train a Convolutional Neural Network (CNN) to recognize these features on input bitmaps. In our demonstration system, these featur…
University of Bonn（波恩大学）；Sapienza University of Rome（罗马大学）
The ability to build maps is a key functionality for the majority of mobile robots. A central ingredient to most mapping systems is the registration or alignment of the recorded sensor data. In this paper, we present a general methodology for photometric registration that can deal with multiple different cues. We provide examples for registering RGBD as well as 3D LIDAR data. In contrast to popular point cloud registration approaches such as ICP our method does not rely on explicit data association and exploits multiple modalities such as raw range and image data streams. Color, depth, and nor…
InPTC: Integrated Planning and Tube-Following Control for Prescribed-Time Collision-Free Navigation of Wheeled Mobile Robots
School of Automation Science and Electrical Engineering, Beihang University（北京航空航天大学自动化科学与电气工程学院）；The Hong Kong Polytechnic University (PolyU)（香港理工大学）；Instituto Tecnológico Autónomo de México (ITAM)（墨西哥自治技术学院）
NORM-Nav: Zero-Shot Mobile Robot Navigation with Natural Language Behavioral Constraints
College of Information Science and Technology, Beijing University of Chemical Technology（北京化工大学信息科学与技术学院）；Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院）；Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and Systems, Macau University of Science and Technology（澳门大学系统工程与智能科学与系统联合实验室）；School of Vehicle and Mobility, Tsinghua University（清华大学车辆与移动系统学院）
Universität Hamburg（汉堡大学）；Chinese Academy of Sciences（中国科学院）；University of CAS（中国科学院大学）；Caltech（加州理工学院）
Crossmodal conflict resolution is crucial for robot sensorimotor coupling through the interaction with the environment, yielding swift and robust behaviour also in noisy conditions. In this paper, we propose a neurorobotic experiment in which an iCub robot exhibits human-like responses in a complex crossmodal environment. To better understand how humans deal with multisensory conflicts, we conducted a behavioural study exposing 33 subjects to congruent and incongruent dynamic audio-visual cues. In contrast to previous studies using simplified stimuli, we designed a scenario with four animated …
Tactile-Proprioceptive Sensor Fusion for Contact Wrench Estimation in Whole-Body Physical Human-Robot Interaction
Department of Robotics and Mechatronics Engineering, DGIST (Daegu Gyeongbuk Institute of Science and Technology)（机器人与机电工程系，DGIST（大邱庆尚科学技术研究所））；Kinetic Intelligent Machine Lab (KIMLAB), University of Illinois Urbana-Champaign（动能智能机器实验室（KIMLAB），伊利诺伊大学厄巴纳-香槟分校）
