A two party haptic guidance controller via a hard rein

RANASINGHE, Anuradha, PENDERS, Jacques, DASGUPTA, Prokar, ALTHOEFER, Kaspar and NANAYAKKARA, Thrishantha (2013). A two party haptic guidance controller via a hard rein. In: Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on. IEEE xplore, 116-122.

IROSpaperNew.pdf - Accepted Version

Download (1MB) | Preview
Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Link to published version:: https://doi.org/10.1109/IROS.2013.6696341


In the case of human intervention in disaster response operations like indoor firefighting, where the environment perception is limited due to thick smoke, noise in the oxygen masks and clutter, not only limit the environmental perception of the human responders, but also causes distress. An intelligent agent (man/machine) with full environment perceptual capabilities is an alternative to enhance navigation in such unfavorable environments. Since haptic communication is the least affected mode of communication in such cases, we consider human demonstrations to use a hard rein to guide blindfolded followers with auditory distraction to be a good paradigm to extract salient features of guiding using hard reins. Based on numerical simulations and experimental systems identification based on demonstrations from eight pairs of human subjects, we show that, the relationship between the orientation difference between the follower and the guider, and the lateral swing patterns of the hard rein by the guider can be explained by a novel 3rd order auto regressive predictive controller. Moreover,by modeling the two party voluntary movement dynamics using a virtual damped inertial model, we were able to model the mutual trust between two parties. In the future, the novel controller extracted based on human demonstrations can be tested on a human-robot interaction scenario to guide a visually impaired person in various applications like fire fighting, search and rescue, medical surgery, etc.

Item Type: Book Section
Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Modelling Research Centre > Microsystems and Machine Vision Laboratory
Identification Number: https://doi.org/10.1109/IROS.2013.6696341
Page Range: 116-122
Depositing User: Helen Garner
Date Deposited: 04 Apr 2014 13:53
Last Modified: 18 Mar 2021 14:02
URI: https://shura.shu.ac.uk/id/eprint/7259

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics