Human-Agent Teaming for Multirobot Control: A Review of Human Factors Issues

The human factors literature on intelligent systems was reviewed in relation to the following: efficient human supervision of multiple robots, appropriate human trust in the automated systems, maintenance of human operator’s situation awareness, individual differences in human-agent (H-A) interaction, and retention of human decision authority. A number of approaches-from flexible automation to autonomous agents-were reviewed, and their advantages and disadvantages were discussed. In addition, two key human performance issues (trust and situation awareness) related to H-A teaming for multirobot control and some promising user interface design solutions to address these issues were discussed. Some major individual differences factors (operator spatial ability, attentional control ability, and gaming experience) were identified that may impact H-A teaming in the context of robotics control. Author affiliation: [Chen, Jessie Y. C.] US Army, Res Lab, Human Res & Engn Directorate, Orlando, FL 32826 USA. [Barnes, Michael J.] US Army, Res Laboratory, Human Res & Engn Directorate, Ft Huachuca, AZ 85613 USA. Reprint Address: Chen, JYC (reprint author), US Army, Res Lab, Human Res & Engn Directorate, Orlando, FL 32826 USA. E-mail Author affiliation: [email protected]; [email protected] Times Cited: 12 Number of references: 198 Tags: Review article, Human-Machine systems Human Interaction With Robot Swarms: A Survey (UK) 2016 Author(s): Kolling, A (Kolling, Andreas); Walker, P (Walker, Phillip); Chakraborty, N (Chakraborty, Nilanjan); Sycara, K (Sycara, Katia); Lewis, M (Lewis, Michael) Source: IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS Volume: 46 Issue: 1 Pages: 9-26 DOI: 10.1109/ THMS.2015.2480801 Published: FEB 2016 ABSTRACT: This paper is the first survey of human-swarm interaction (HSI) and identifies the core concepts needed to design a human-swarm system. We first present the basics of swarm robotics. Then, we introduce HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems. Next, we introduce the interface between swarm and operator and identify challenges and solutions relating to human-swarm communication, state estimation and visualization, and human control of swarms. For the latter, we develop a taxonomy of control methods that enable operators to control swarms effectively. Finally, we synthesize the results to highlight remaining challenges, unanswered questions, and open problems for HSI, as well as how to address them in future works. Author affiliation: [Kolling, Andreas] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S10 2TN, S Yorkshire, England. [Walker, Phillip; Lewis, Michael] Univ Pittsburgh, Dept Informat Sci, Pittsburgh, PA 15260 USA. [Chakraborty, Nilanjan] SUNY Stony Brook, Dept Mech Engn, Stony Brook, NY 11790 USA. [Sycara, Katia] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA. Reprint Address: Kolling, A (reprint author), Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S10 2TN, S Yorkshire, England. E-mail Author affiliation: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] Times Cited: 0 Number of references: 140 Tags: Review article, Human-Machine Systems IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS: Year in Review for 2014 (USA) 2014 Author(s): Bass, EJ (Bass, Ellen J.) Source: IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS Volume: 45 Issue: 1 Pages: 1-12 DOI: 10.1109/ THMS.2014.2385911 Published: FEB 2015 Author affiliation: [Bass, Ellen J.] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA. [Bass, Ellen J.] Drexel Univ, Coll Nursing & Hlth Profess, Philadelphia, PA 19104 USA. Reprint Address: Bass, EJ (reprint author), Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA. E-mail Author affiliation: [email protected] TECHNICAL ARTICLES