The Classification and New Trends of Shared Control Strategies in Telerobotic Systems: A Survey.

Journal: IEEE transactions on haptics
Published Date:

Abstract

Shared control, which permits a human operator and an autonomous controller to share the control of a telerobotic system, can reduce the operator's workload and/or improve performances during the execution of tasks. Due to the great benefits of combining the human intelligence with the higher power/precision abilities of robots, the shared control architecture occupies a wide spectrum among telerobotic systems. Although various shared control strategies have been proposed, a systematic overview to tease out the relation among different strategies is still absent. This survey, therefore, aims to provide a big picture for existing shared control strategies. To achieve this, we propose a categorization method and classify the shared control strategies into 3 categories: Semi-Autonomous control (SAC), State-Guidance Shared Control (SGSC), and State-Fusion Shared Control (SFSC), according to the different sharing ways between human operators and autonomous controllers. The typical scenarios in using each category are listed and the advantages/disadvantages and open issues of each category are discussed. Then, based on the overview of the existing strategies, new trends in shared control strategies, including the "autonomy from learning" and the "autonomy-levels adaptation," are summarized and discussed.

Authors

  • Gaofeng Li
  • Qiang Li
    Department of Dermatology, Air Force Medical Center, PLA, Beijing, People's Republic of China.
  • Chenguang Yang
    Department of Computer Science, University of Liverpool, Liverpool, United Kingdom.
  • Yuan Su
    Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health Institute of Nutrition and Health, China Agricultural University, Beijing, 100083, China.
  • Zuqiang Yuan
  • Xinyu Wu
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.