Salient Feature of Haptic-Based Guidance of People in Low Visibility Environments Using Hard Reins

Abstract

Abstract-This paper presents salient features of humanhuman interaction where one person with limited auditory and visual perception of the environment (a follower) is guided by an agent with full perceptual capabilities (a guider) via a hard rein along a given path. We investigate several salient features of the interaction between the guider and the follower such as a) the order of an autoregressive control policy that maps states of the follower to actions of the guider, b) how the guider may modulate the pulling force in response to the confidence level of the follower, and c) how learning may successively apportion the responsibility of control across different muscles of the guider. Based on experimental systems identification on human demonstrations from ten pairs of naive subjects, we show that guiders tend to adopt a 3 rd order auto-regressive predictive control policy and followers tend to adopt 2 nd order reactive control policy. Moreover, the extracted guider's control policy was implemented and validated by human-robot interaction experiments. By modeling the follower's dynamics with a time varying virtual damped inertial system, we found that it is the coefficient of virtual damping which is most sensitive to the confidence level of the follower. We used these experimental insights to derive a novel controller that integrates an optimal order control policy with a push/pull force modulator in response to the confidence level of the follower monitored using a time varying virtual damped inertial model.Index Terms-Human robot interaction, hard rein, haptic communication, predictive and reactive control policies.

Fuzzy logic controller for stabilization of biped robot gait

“…The sample contained 2910 values of the input triple. The ANFIS method was chosen due to the success of the neuro-fuzzy approach in the tasks of mobile robotics [3][4][5][6].…”

Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

“…The developed fuzzy controller manages at the same time navigation and obstacle avoidance tasks. Many academic studies propose the fuzzy logic theory as a solution to control mobile robots [ 8 – 11 ]. The basic structure of the fuzzy controller is composed of three blocks: the fuzzification, inference, and defuzzification.…”

Investigating spatial guidance for a cooperative handheld robot

“…Ranasinghe et al [9] use haptic feedback to guide users in low visibility environments. The authors performed an experiment where a participant would guide a user along a path by pulling on a rigid link that they both held.…”