"I call shotgun!": an evaluation of mixed-initiative control for novice users of a search and rescue robot

Bruemmer, David J.; Boring, Ronald L.; Few, Douglas A.; Marble, Julie L.; Walton, Miles

doi:10.1109/icsmc.2004.1400764

Cited by 23 publications

(11 citation statements)

References 6 publications

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“…Much of the published experimental work does not carefully control for possible confounding factors. These factors can vary from partially uncontrolled test environments (as in [10]), up to the absence of standardized training for human test-subjects as in [8], [11], [12]. It is particularly important to control for the training and experience of human test-subjects, as these factors are known to affect overall robot operating performance [13], [14].…”

Section: Related Workmentioning

confidence: 99%

Experimental analysis of a variable autonomy framework for controlling a remotely operating mobile robot

Chiou

Bieksaite

Hawes

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Section: Related Workmentioning

confidence: 99%

Experimental analysis of a variable autonomy framework for controlling a remotely operating mobile robot

Chiou

Bieksaite

Hawes

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…Previous work on mixed initiative interactions has primarily focused on the development of effective graphical user interfaces or haptic feedback to relay task-dependent data to the human, and to relay human control information to the automatic controller or autonomous, robotic agent (e.g., [5], [6], [7], [8], [9], [10]). In this paper, we largely ignore this issue.…”

Section: Introductionmentioning

confidence: 99%

Less Is More: Mixed-Initiative Model-Predictive Control With Human Inputs

2013

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This paper presents a new method for injecting human inputs in mixed initiative interactions between humans and robots. The method is based on a model predictive control (MPC) formulation, which inevitably involves predicting the system (robot dynamics as well as human inputs) into the future. These predictions are complicated by the fact that the human is interacting with the robot, causing the prediction method itself to have an effect on future human inputs. We investigate and develop different prediction schemes, including fixed and variable horizon MPCs and human input estimators of different orders. Through a search-and-rescue-inspired human operator study, we arrive at the conclusion that the simplest prediction methods outperform the more complex ones, i.e., in this particular case, less is indeed more.Index Terms-human-robot interaction, model-predictive control, mixed initiative initeractions.

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“…We believe that the participants in this study represent a random sampling of the population. In any case, a previous study with our control architecture indicates that there are no statistically significant effects for age or gender pertaining to users of our system [14].…”

Section: Participantsmentioning

confidence: 66%

“…In contrast to our previous experiments [7,14] which were designed to determine the benefits of different levels of robot initiative, this experiment focused on a quantitative analysis of performance, workload, error, and feeling of control collected during the exploration task. Based on our previous experiment with novice users [14] it was assumed no statistical performance differences exist across age or gender differences.…”

Section: Resultsmentioning

confidence: 99%

"Turn Off the Television!": Real-World Robotic Exploration Experiments with a Virtual 3-D Display

Bruemmer

Few

Walton

et al.

Proceedings of the 38th Annual Hawaii International Conference on System Sciences

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In order to apply mobile robots to a new range of applications, we require control architectures and interfaces that support symbiotic interaction. Remote deployment of mobile robots offers one of the most compelling opportunities to merge human intelligence with machine proficiency. This paper discusses a mixedinitiative control strategy based not on video, but on an abstracted, collaborative workspace-a 3-D, video-game representation constructed on-the-fly-that promotes situation-awareness and efficient tasking. The new interface requires orders of magnitude less bandwidth than teleoperation and permits transmission ranges of thousands of miles. Unlike video, which offers only a 1 st person, local environment perspective, the 3-D interface changes perspective to support changing levels of operator involvement and robot autonomy. The humanparticipant study presented evaluates the effectiveness of this interaction substrate on a remote exploration task. Results indicate that this new tool for interfacing humans and intelligent robots can reduce human error, support changing levels of human workload, promote human trust, and enable a spectrum of remote robotic applications which have never before been possible.

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"I call shotgun!": an evaluation of mixed-initiative control for novice users of a search and rescue robot

Cited by 23 publications

References 6 publications

Experimental analysis of a variable autonomy framework for controlling a remotely operating mobile robot

Experimental analysis of a variable autonomy framework for controlling a remotely operating mobile robot

Less Is More: Mixed-Initiative Model-Predictive Control With Human Inputs

"Turn Off the Television!": Real-World Robotic Exploration Experiments with a Virtual 3-D Display

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