Service Robots for Citizens of the Future

被引:13
作者
Torras, Carme [1 ]
机构
[1] UPC, CSIC, Inst Robot & Informat Ind, Barcelona, Spain
关键词
MANIPULATION;
D O I
10.1017/S1062798715000393
中图分类号
K9 [地理];
学科分类号
0705 ;
摘要
Robots are no longer confined to factories; they are progressively spreading to urban, social and assistive domains. In order to become handy co-workers and helpful assistants, they must be endowed with quite different abilities from their industrial ancestors. Research on service robots aims to make them intrinsically safe to people, easy to teach by non-experts, able to manipulate not only rigid but also deformable objects, and highly adaptable to non-predefined and dynamic environments. Robots worldwide will share object and environmental models, their acquired knowledge and experiences through global databases and, together with the internet of things, will strongly change the citizens' way of life in so-called smart cities. This raises a number of social and ethical issues that are now being debated not only within the Robotics community but by society at large.
引用
收藏
页码:17 / 30
页数:14
相关论文
共 36 条
  • [11] De Luca A, 2012, P IEEE RAS-EMBS INT, P288, DOI 10.1109/BioRob.2012.6290917
  • [12] Self-calibration of a space robot
    deAngulo, VR
    Torras, C
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1997, 8 (04): : 951 - 963
  • [13] Doumanoglou A, 2014, IEEE INT CONF ROBOT, P987, DOI 10.1109/ICRA.2014.6906974
  • [14] Body Schema in Robotics: A Review
    Hoffmann, Matej
    Marques, Hugo Gravato
    Arieta, Alejandro Hernandez
    Sumioka, Hidenobu
    Lungarella, Max
    Pfeifer, Rolf
    [J]. IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT, 2010, 2 (04) : 304 - 324
  • [15] Challenges for robot manipulation in human environments - Developing robots that perform useful work in everyday settings
    Kemp, Charles C.
    Edsinger, Aaron
    Torres-Jara, Eduardo
    [J]. IEEE ROBOTICS & AUTOMATION MAGAZINE, 2007, 14 (01) : 20 - 29
  • [16] Martinez D., 2015, IEEE RSJ IN IN PRESS
  • [17] Martinez D., 2015, ARTIFICIAL IN PRESS
  • [18] Paraschos A., 2013, C NEUR INF PROC SYST, P2616
  • [19] Reinforcement learning of motor skills with policy gradients
    Peters, Jan
    Schaal, Stefan
    [J]. NEURAL NETWORKS, 2008, 21 (04) : 682 - 697
  • [20] Learning RGB-D descriptors of garment parts for informed robot grasping
    Ramisa, Arnau
    Alenya, Guiliem
    Moreno-Noguer, Francesc
    Torras, Carme
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2014, 35 : 246 - 258