Traction awareness through haptic feedback for the teleoperation of UGVs*

Teleoperation of Unmanned Ground Vehicles (UGVs) is dependent on several factors as the human operator is physically detached from the UGV. This paper focuses on situations where a UGV designed for search and rescue loses traction, thus becoming unable to comply with the operator's commands. In such situations, the lack of Situation Awareness (SA) may lead to an incorrect and inefficient response to the current UGV state usually confusing and frustrating the human operator. The exclusive use of visual information to simultaneously perform the main task (e.g. search and rescue) and to be aware of possible impediments to UGV operation, such as loss of traction, becomes a very challenging task for a single human operator. We address the challenge of unburdening the visual channel by using other human senses to provide multimodal feedback in UGV teleoperation. To achieve this goal we present a teleoperation architecture comprising (1) a laser-based traction detector module, to discriminate between traction losses (stuck and sliding) and (2) a haptic interface to convey the detected traction state to the human operator through different types of tactile stimuli provided by three haptic devices (E-Vita, Traction Cylinder and Vibrotactile Glove). We also report the experimental results of a user study to evaluate to what extent this new feedback modality improves the user SA regarding the UGV traction state. Statistically significant results were found supporting the hypothesis that two of the haptic devices improved the comprehension of the traction state of the UGV when comparing to exclusively visual modality.info:eu-repo/semantics/acceptedVersio

SPATIAL PERCEPTION AND ROBOT OPERATION: THE RELATIONSHIP BETWEEN VISUAL SPATIAL ABILITY AND PERFORMANCE UNDER DIRECT LINE OF SIGHT AND TELEOPERATION

This dissertation investigated the relationship between the spatial perception abilities of operators and robot operation under direct-line-of-sight and teleoperation viewing conditions. This study was an effort to determine if spatial ability testing may be a useful tool in the selection of human-robot interaction (HRI) operators. Participants completed eight cognitive ability measures and operated one of four types of robots under tasks of low and high difficulty. Performance for each participant was tested during both direct-line-of-sight and teleoperation. These results provide additional evidence that spatial perception abilities are reliable predictors of direct-line-of-sight and teleoperation performance. Participants in this study with higher spatial abilities performed faster, with fewer errors, and less variability. In addition, participants with higher spatial abilities were more successful in the accumulation of points. Applications of these findings are discussed in terms of teleoperator selection tools and HRI training and design recommendations with a human-centered design approach

A State Estimation Approach for a Skid-Steered Off-Road Mobile Robot

This thesis presents a novel state estimation structure, a hybrid extended Kalman filter/Kalman filter developed for a skid-steered, six-wheeled, ARGO® all-terrain vehicle (ATV). The ARGO ATV is a teleoperated unmanned ground vehicle (UGV) custom fitted with an inertial measurement unit, wheel encoders and a GPS. In order to enable the ARGO for autonomous applications, the proposed hybrid EKF/KF state estimator strategy is combined with the vehicle’s sensor measurements to estimate key parameters for the vehicle. Field experiments in this thesis reveal that the proposed estimation structure is able to estimate the position, velocity, orientation, and longitudinal slip of the ARGO with a reasonable amount of accuracy. In addition, the proposed estimation structure is well-suited for online applications and can incorporate offline virtual GPS data to further improve the accuracy of the position estimates. The proposed estimation structure is also capable of estimating the longitudinal slip for every wheel of the ARGO, and the slip results align well with the motion estimate findings

Human-robot interaction in the context of simulated route reconnaissance missions

The goal of this research was to examine the ways in which human operators interact with simulated semiautonomous unmanned ground vehicles (UGVs), semiautonomous unmanned aerial vehicles (UAVs), and teleoperated UGVs (Teleop). Robotic operators performed parallel route reconnaissance missions with each platform alone and with all three platforms. When given all three platforms, participants failed to detect more targets than when given only the UAV or UGV; they were also less likely to complete their mission in the allotted time. Target detection during missions was the poorest with the Teleop alone, likely because of the demands of remote driving. Spatial ability was found to be a good predictor of target-detection performance. However, slowing sensor feed video frame rate or the imposition of a short response latency (250 ms) between Teleop control and Teleop reaction failed to affect target-detection performance significantly. Nevertheless, these video image manipulations did influence assessment of system usability

Human-Robot Interaction In The Context Of Simulated Route Reconnaissance Missions

The goal of this research was to examine the ways in which human operators interact with simulated semiautonomous unmanned ground vehicles (UGVs), semiautonomous unmanned aerial vehicles (UAVs), and teleoperated UGVs (Teleop). Robotic operators performed parallel route reconnaissance missions with each platform alone and with all three platforms. When given all three platforms, participants failed to detect more targets than when given only the UAV or UGV; they were also less likely to complete their mission in the allotted time. Target detection during missions was the poorest with the Teleop alone, likely because of the demands of remote driving. Spatial ability was found to be a good predictor of target-detection performance. However, slowing sensor feed video frame rate or the imposition of a short response latency (250 ms) between Teleop control and Teleop reaction failed to affect target-detection performance significantly. Nevertheless, these video image manipulations did influence assessment of system usability