Affecting operator trust in intelligent multirobot surveillance systems

Abstract

Homeland safety and security will increasingly depend upon autonomous unmanned vehicles as a method of assessing and maintaining situational awareness. As autonomous team algorithms evolve toward requiring less human intervention, it may be that having an "operator-in-the-loop" becomes the ultimate goal in utilizing autonomous teams for surveillance. However studies have shown that trust plays a factor in how effectively an operator can work with autonomous teammates.In this work, we study mechanisms that look at autonomy as a system and not as the sum of individual actions. First, we conjecture that if the operator understands how the team autonomy is designed that the user would better trust that the system will contribute to the overall goal. Second, we focus on algorithm input criteria as being linked to operator perception and trust. We focus on adding a time-varying spatial projection of areas in the ROI that have been unseen for more than a set duration (STEC). Studies utilize a custom test bed that allows users to interact with a surveillance team to find a target in the region of interest. Results show that while algorithm training had an adverse effect, projecting salient team/surveillance state had a statistically significant impact on trust and did not negatively affect workload or performance. This result may point at a mechanism for improving trust through visualizing states as used in the autonomous algorithm.

Let’s Work Together: A Meta-Analysis on Robot Design Features That Enable Successful Human–Robot Interaction at Work

“…First, a design of interface and controller that facilitates communication through high visibility of affordances of the input device, sufficient feedback about the current status of the robot, and adaptable and autonomous controllers generally benefits successful HRI. The studies included in this meta-analysis provide detailed examples for the practical application of different forms of highly visible affordances (e.g., Radmard et al, 2015; Walker et al, 2015; Will et al, 2013), feedback (e.g., Harder et al, 2016; Hou & Mahony, 2016; Zhang & Adams, 2012), possibilities to design adaptable controllers (e.g., Gopinathan et al, 2017; Hoffman & Breazeal, 2007; Huang & Mutlu, 2016), and different degrees of autonomy (e.g., Chen et al, 2013; Dawson et al, 2015; Geiskkovitch et al, 2015). Robot designers might use this overview as a starting point for designing robots that foster successful HRI through well-designed communication.…”

Multirobot Confidence and Behavior Modeling: An Evaluation of Semiautonomous Task Performance and Efficiency

“…Research toward interaction with multiple semiautonomous robots includes task switching and operator attention allocation [52][53][54], such as identifying where an operator should focus and influencing the operator's behavior accordingly via visual cues in a graphical user interface [55]. Other work includes determining which aspects of a given task are most suitable for automation [16], measuring and influencing operator trust in team autonomy [19], using intelligent agents to help human operators manage a team of multiple robots [13], and augmented reality interfaces to integrate information from multiple sources and project it into a view of the real world using a common frame of reference [35,56,57].…”

“…Researchers have long sought to enable multiple robots working together as a team [1][2][3][4][5][6][7][8][9][10] to perform distributed tasks such as area exploration, search, and surveillance [11][12][13][14][15][16][17][18][19] and complex tasks in hostile conditions such as the assembly of structures in orbit, lunar, and planetary environments [20][21][22][23][24][25][26]. Advances in sensing, computing, and materials may make fully autonomous multirobot systems possible in certain circumstances.…”

Shaping of Shared Autonomous Solutions With Minimal Interaction

“…There is, however, some work by Crossman et al ( 2012 ), Alonso-Mora et al ( 2015 ), and Dawson et al ( 2015 ) that does looks toward human interaction with autonomous planning systems. We see two fundamental and contrasting approaches that are taken.…”