Human-Robot Trust Integrated Task Allocation and Symbolic Motion Planning for Heterogeneous Multi-Robot Systems

Zheng, Huanfei; Liao, Zhanrui; Wang, Yue

doi:10.1115/dscc2018-9161

Cited by 9 publications

(5 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other works made some variations but generally followed a similar structure [180]- [182]. Following a similar structure as in Figure 7, a DBN trust model for multi-robot symbolic robot motion planning 12 with a human-in-the-loop was developed [180], [181]. Besides the robot performance, the DBN trust model also included human performance and faults as causal inputs.…”

Section: Definition 10 [172]mentioning

confidence: 99%

Human Trust in Robots: A Survey on Trust Models and Their Controls/Robotics Applications

Wang,

Li,

Zheng

et al. 2024

IEEE Open J. Control. Syst.

Self Cite

View full text Add to dashboard Cite

Trust model is a topic that first gained interest in organizational studies and then human factors in automation. Thanks to recent advances in human-robot interaction (HRI) and human-autonomy teaming, human trust in robots has gained growing interest among researchers and practitioners. This article focuses on a survey of computational models of human-robot trust and their applications in robotics and robot controls. The motivation is to provide an overview of the state-of-the-art computational methods to quantify trust so as to provide feedback and situational awareness in HRI. Different from other existing survey papers on human-robot trust models, we seek to provide in-depth coverage of the trust model categorization, formulation, and analysis, with a focus on their utilization in robotics and robot controls. The paper starts with a discussion of the difference between human-robot trust with general agent-agent trust, interpersonal trust, and human trust in automation and machines. A list of impacting factors for human-robot trust and different trust measurement approaches, and their corresponding scales are summarized. We then review existing computational human-robot trust models and discuss the pros and cons of each category of models. These include performance-centric algebraic, time-series, Markov decision process (MDP)/Partially Observable MDP (POMDP)-based, Gaussian-based, and dynamic Bayesian network (DBN)-based trust models. Following the summary of each computational human-robot trust model, we examine its utilization in robot control applications, if any. We also enumerate the main limitations and open questions in this field and discuss potential future research directions.

show abstract

Section: Definition 10 [172]mentioning

confidence: 99%

Human Trust in Robots: A Survey on Trust Models and Their Controls/Robotics Applications

Wang,

Li,

Zheng

et al. 2024

IEEE Open J. Control. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Collision avoidance for multi-robot systems should be investigated to ensure the safety of human collaborators [133,134]. In addition, task allocation for multi-robot systems and human workers can allow humans to build trust in the robot system and achieve a safe working environment [135,136].…”

Section: Future Directionsmentioning

confidence: 99%

Trends in Robotics Research in Occupational Safety and Health: A Scientometric Analysis and Review

Liang

Cheng

2023

IJERPH

View full text Add to dashboard Cite

Robots have been deployed in workplaces to assist, work alongside, or collaborate with human workers on various tasks, which introduces new occupational safety and health hazards and requires research efforts to address these issues. This study investigated the research trends for robotic applications in occupational safety and health. The scientometric method was applied to quantitatively analyze the relationships between robotics applications in the literature. The keywords “robot”, “occupational safety and health”, and their variants were used to find relevant articles. A total of 137 relevant articles published during 2012–2022 were collected from the Scopus database for this analysis. Keyword co-occurrence, cluster, bibliographic coupling, and co-citation analyses were conducted using VOSviewer to determine the major research topics, keywords, co-authorship, and key publications. Robot safety, exoskeletons and work-related musculoskeletal disorders, human–robot collaboration, and monitoring were four popular research topics in the field. Finally, research gaps and future research directions were identified based on the analysis results, including additional efforts regarding warehousing, agriculture, mining, and construction robots research; personal protective equipment; and multi-robot collaboration. The major contributions of the study include identifying the current trends in the application of robotics in the occupational safety and health discipline and providing pathways for future research in this discipline.

show abstract

“…A more general approach is to directly model the human's dynamic trust in the robot. Work in this area has focused on two problems: (i) estimating trust based on observations of the human's behavior [18,27,[57][58][59][60][61][62][63][64] and (ii) utilizing the estimate of trust to guide robot behavior [27,58,[65][66][67][68][69].…”

Section: Computational Trust Modelsmentioning

confidence: 99%

“…This Bayesian approach to reasoning about trust has also been explored non-parametrically using Gaussian processes [63]. Lastly, this framework has also been extended to model a user's trust in multiple robots [62], thus paving the way for dynamic trust modeling in multi-agent settings.…”

Section: Computational Trust Modelsmentioning

confidence: 99%

Trust in Robots: Challenges and Opportunities

2020

View full text Add to dashboard Cite

Purpose of Review To assess the state-of-the-art in research on trust in robots and to examine if recent methodological advances can aid in the development of trustworthy robots. Recent Findings While traditional work in trustworthy robotics has focused on studying the antecedents and consequences of trust in robots, recent work has gravitated towards the development of strategies for robots to actively gain, calibrate, and maintain the human user's trust. Among these works, there is emphasis on endowing robotic agents with reasoning capabilities (e.g., via probabilistic modeling). Summary The state-of-the-art in trust research provides roboticists with a large trove of tools to develop trustworthy robots. However, challenges remain when it comes to trust in real-world human-robot interaction (HRI) settings: there exist outstanding issues in trust measurement, guarantees on robot behavior (e.g., with respect to user privacy), and handling rich multidimensional data. We examine how recent advances in psychometrics, trustworthy systems, robot-ethics, and deep learning can provide resolution to each of these issues. In conclusion, we are of the opinion that these methodological advances could pave the way for the creation of truly autonomous, trustworthy social robots.

show abstract

Human-Robot Trust Integrated Task Allocation and Symbolic Motion Planning for Heterogeneous Multi-Robot Systems

Cited by 9 publications

References 17 publications

Human Trust in Robots: A Survey on Trust Models and Their Controls/Robotics Applications

Human Trust in Robots: A Survey on Trust Models and Their Controls/Robotics Applications

Trends in Robotics Research in Occupational Safety and Health: A Scientometric Analysis and Review

Trust in Robots: Challenges and Opportunities

Contact Info

Product

Resources

About