On-The-Go Robot-to-Human Handovers with a Mobile Manipulator

He, Kerry; Simini, Pradeepsundar; Chan, Wesley P.; Kulić, Dana; Croft, Elizabeth A.; Cosgun, Akansel

doi:10.1109/ro-man53752.2022.9900642

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…For example, some studies use terms like stress [19], strain [20], and frustration [21] without providing clear definitions, making it inaccurate to group them together under one umbrella term. Likewise, the legibility [22] and predictability [23] of a robot's motion, and physical ergonomics [24], physical comfort [22], fatigue [25], and health and safety [26] are two sets of examples of the different human factors that overlap but cannot be lumped under a single comprehensive term within the set. Additionally, perceived enjoyment [21] and enjoyability [27], and psychological safety, mental safety, and subjective safety [8] are also examples of the human factors that are distinct but interconnected.…”

Section: Literature Gapmentioning

confidence: 99%

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Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review

Abdulazeem,

2023

Sensors

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As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human–robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing the studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human–robot interaction (pHRI), noted the factors typically addressed together, and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on the measurable data for each human factor. We also formed a map of the common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI studies (when the physical contact is mediated via a third item) often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on the human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address the quantification approaches based on measurable data.

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Section: Literature Gapmentioning

confidence: 99%

“…In a general context where handovers may occur in domestic and industrial environments, a study investigated handovers using a mobile manipulator that transferred objects to humans without stopping [23].…”

Section: Indirect Phrimentioning

confidence: 99%

Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review

Abdulazeem,

2023

Sensors

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Robot Gaze During Autonomous Navigation and Its Effect on Social Presence

Chan

Cosgun

et al. 2023

Int J of Soc Robotics

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As robots have become increasingly common in human-rich environments, it is critical that they are able to exhibit social cues to be perceived as a cooperative and socially-conformant team member. We investigate the effect of robot gaze cues on people’s subjective perceptions of a mobile robot as a socially present entity in three common hallway navigation scenarios. The tested robot gaze behaviors were path-oriented (looking at its own future path), or human-oriented (looking at the nearest person), with fixed-gaze as the control. We conduct a real-world study with 36 participants who walked through the hallway, and an online study with 233 participants who were shown simulated videos of the same scenarios. Our results suggest that the preferred gaze behavior is scenario-dependent. Human-oriented gaze behaviors which acknowledge the presence of the human are generally preferred when the robot and human cross paths. However, this benefit is diminished in scenarios that involve less implicit interaction between the robot and the human.

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An Architecture for Reactive Mobile Manipulation On-The-Move

Ben

Lehnert

Leitner³

et al. 2023

2023 IEEE International Conference on Robotics and Automation (ICRA)

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We present a reactive base control method that enables high performance mobile manipulation on-the-move in environments with static and dynamic obstacles. Performing manipulation tasks while the mobile base remains in motion can significantly decrease the time required to perform multistep tasks, as well as improve the gracefulness of the robot's motion. Existing approaches to manipulation on-the-move either ignore the obstacle avoidance problem or rely on the execution of planned trajectories, which is not suitable in environments with dynamic objects and obstacles. The presented controller addresses both of these deficiencies and demonstrates robust performance of pick-and-place tasks in dynamic environments. The performance is evaluated on several simulated and real-world tasks. On a real-world task with static obstacles, we outperform an existing method by 48% in terms of total task time. Further, we present real-world examples of our robot performing manipulation tasks onthe-move while avoiding a second autonomous robot in the workspace. See benburgesslimerick.github.io/MotM-BaseControl for supplementary materials.

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On-The-Go Robot-to-Human Handovers with a Mobile Manipulator

Cited by 6 publications

References 29 publications

Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review

Human Factors Considerations for Quantifiable Human States in Physical Human–Robot Interaction: A Literature Review

Robot Gaze During Autonomous Navigation and Its Effect on Social Presence

An Architecture for Reactive Mobile Manipulation On-The-Move

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