Experience of using a haptic interface to follow a robot without visual feedback

Search and rescue operations are often undertaken in smoke filled and noisy environments in which rescue teams must rely on haptic feedback for navigation and safe exit. In this paper, we discuss designing and evaluating a haptic interface to enable a human being to follow a robot through an environment with no-visibility. We first discuss the considerations that have led to our current interface design. The second part of the paper describes our testing procedure and the results of our first tests. Based on these results we discuss future improvements of our design

Human robot interaction in the absence of visual and aural feedback: Exploring the haptic sense

The potential of robot swarms for Search and Rescue has been shown by the Guardians project (EU, 2006-2010); however the project also showed the problem of human robot interaction in smoky (non-visibility) and noisy conditions. The REINS project (UK, 2011-2015) focused on human robot interaction in such conditions. This paper briefly reviews the scientific context relevant for designing a haptic interface for human robot navigation and examines what we have achieved since then. The aim is to put the major design issues into context

Sample-Efficient Training of Robotic Guide Using Human Path Prediction Network

Training a robot that engages with people is challenging, because it is expensive to involve people in a robot training process requiring numerous data samples. This paper proposes a human path prediction network (HPPN) and an evolution strategy-based robot training method using virtual human movements generated by the HPPN, which compensates for this sample inefficiency problem. We applied the proposed method to the training of a robotic guide for visually impaired people, which was designed to collect multimodal human response data and reflect such data when selecting the robot's actions. We collected 1,507 real-world episodes for training the HPPN and then generated over 100,000 virtual episodes for training the robot policy. User test results indicate that our trained robot accurately guides blindfolded participants along a goal path. In addition, by the designed reward to pursue both guidance accuracy and human comfort during the robot policy training process, our robot leads to improved smoothness in human motion while maintaining the accuracy of the guidance. This sample-efficient training method is expected to be widely applicable to all robots and computing machinery that physically interact with humans

Haptic Interaction with a Guide Robot in Zero Visibility

Search and rescue operations are often undertaken in dark and noisy environment in which rescue team must rely on haptic feedback for exploration and safe exit. However, little attention has been paid specifically to haptic sensitivity in such contexts or the possibility of enhancing communicational proficiency in the haptic mode as a life-preserving measure. The potential of root swarms for search and rescue has been shown by the Guardians project (EU, 2006-2010); however the project also showed the problem of human robot interaction in smoky (non-visibility) and noisy conditions. The REINS project (UK, 2011-2015) focused on human robot interaction in such conditions. This research is a body of work (done as a part of he REINS project) which investigates the haptic interaction of a person wit a guide robot in zero visibility. The thesis firstly reflects upon real world scenarios where people make use of the haptic sense to interact in zero visibility (such as interaction among firefighters and symbiotic relationship between visually impaired people and guide dogs). In addition, it reflects on the sensitivity and trainability of the haptic sense, to be used for the interaction. The thesis presents an analysis and evaluation of the design of a physical interface (Designed by the consortium of the REINS project) connecting the human and the robotic guide in poor visibility conditions. Finally, it lays a foundation for the design of test cases to evaluate human robot haptic interaction, taking into consideration the two aspects of the interaction, namely locomotion guidance and environmental exploration