Spatial augmented reality as a method for a mobile robot to communicate intended movement

Our work evaluates a mobile robot’s ability to communicate intended movements to humans via projection of visual arrows and a simplified map. Humans utilize a variety of techniques to signal intended movement in a co-occupied space. We evaluated an augmented reality projection provided by the robot. The projection is on the floor and consists of arrows and a simplified map. Two pilots and one quasi-experiment were conducted to examine the effectiveness of visual projection of arrows by a robot for signaling intended movement. The pilot work demonstrates the effectiveness of utilizing arrows as a communication medium. The experiment examined the effectiveness of a simplified map and arrows for signaling the short-, mid-range, and long-term intended movement. Two pilot experiments confirm that arrows are an effective symbol for a robot to use to signal intent. A field experiment demonstrates that a robot can use a projected arrow and simplified map to signal its intended movement and people understand the projection for upcoming short-, medium-, and long-term movement. Augmented reality, such as projected arrows and simplified map, are an effective tool for robots to use when signaling their upcoming movement to humans. Telepresence robots in organizations, museum docents, information kiosks, hospital assistants, factories, and as members of search and rescue teams are typical applications where mobile robots reside and interact with people.     

Expressing reactive emotion based on multimodal emotion recognition for natural conversation in human–robot interaction*

Human–human interaction consists of various nonverbal behaviors that are often emotion-related. To establish rapport, it is essential that the listener respond to reactive emotion in a way that makes sense given the speaker's emotional state. However, human–robot interactions generally fail in this regard because most spoken dialogue systems play only a question-answer role. Aiming for natural conversation, we examine an emotion processing module that consists of a user emotion recognition function and a reactive emotion expression function for a spoken dialogue system to improve human–robot interaction. For the emotion recognition function, we propose a method that combines valence from prosody and sentiment from text by decision-level fusion, which considerably improves the performance. Moreover, this method reduces fatal recognition errors, thereby improving the user experience. For the reactive emotion expression function, the system's emotion is divided into emotion category and emotion level, which are predicted using the parameters estimated by the recognition function on the basis of distributions inferred from human–human dialogue data. As a result, the emotion processing module can recognize the user's emotion from his/her speech, and expresses a reactive emotion that matches. Evaluation with ten participants demonstrated that the system enhanced by this module is effective to conduct natural conversation.     

Asymmetric Velocity Moderation for human-safe robot control

With the increasing physical proximity of human–robot interaction, ensuring that robots do not harm surrounding humans has become crucial. Therefore, we propose asymmetric velocity moderation as a low-level controller for robotic systems to enforce human-safe motions. While our method prioritizes human safety, it also maintains the robot’s efficiency. Our proposed method restricts the robot’s speed according to (1) the displacement vector between human and robot, and (2) the robot’s velocity vector. That is to say, both the distance and the relative direction of movement are taken into account to restrict the robot’s motion. Through real-robot and simulation experiments using simplified HRI scenarios and dangerous situations, we demonstrate that our method is able to maintain the robot’s efficiency without undermining human safety.     

UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment

A military reconnaissance environment was simulated to examine the performance of ground robotics operators who were instructed to utilise streaming video from an unmanned aerial vehicle (UAV) to navigate his/her ground robot to the locations of the targets. The effects of participants' spatial ability on their performance and workloadwere also investigated. Results showed that participants' overall performance (speed and accuracy) was better when she/he had access to images from larger UAVs with fixed orientations, compared with other UAV conditions (baseline- no UAV, micro air vehicle and UAV with orbiting views). Participants experienced the highest workload when the UAV was orbiting. Those individuals with higher spatial ability performed significantly better and reported less workload than those with lower spatial ability.

The results of the current study will further understanding of ground robot operators' target search performance based on streaming video from UAVs. The results will also facilitate the implementation of ground/air robots in military environments and will be useful to the future military system design and training community.     

Fuzzy-based-admittance controller for safe natural human–robot interaction

ABSTRACT

In recent years, a great amount of research on physical human–robot interaction has been conducted, and mainly concentrated on safety issues to minimize the risk of accidents to the operator during the cooperation between human and robot. Unfortunately, the identification of inertia and damping matrices in the dynamic admittance model is time-consuming, which is still an open problem of previous admittance controllers. Additionally, the natural cooperation is that cooperative movements are implemented in every degree of freedom in space, which is rarely concerned while it is important to implement more complex cooperative movements, and to help operator feels naturally during the cooperation. This paper presents an alternative admittance controller based on inference mechanism of fuzzy logic to eliminate the identification of inertia and damping matrices during the process of controller formulation in which the end-effector’s velocity is adaptively adjusted via external wrench (force/torque measured by a sensor mounted on end-effector) and power transmitted by the robot. Moreover, the proposed controller also considers end-effector’s full DOF to guarantee the natural human–robot interaction. The fuzzy-admittance controller is evaluated by an experimental set-up of teaching task using 6-DOF manipulator in which manipulator moves passively via the human impact on real-time force/torque sensor mounted on end-effector.     

Designing an API at an appropriate abstraction level for programming social robot applications

Whilst robots are increasingly being deployed as social agents, it is still difficult to program them to interact socially. To create usable tools for programming these robots, tool developers need to know what abstraction levels are appropriate for programming social robot applications. We explore this through the iterative design and evaluation of an API for programming social robots. The results show that high level primitives, with a close mapping to social interaction, are suitable for programming social robot applications. However, the abstraction level should not be so high that it takes away too much control from programmers. This has the potential to enable programmers to produce high quality social robot applications with less programming effort.     

Utility of stereoscopic displays for indirect-vision driving and robot teleoperation

The effectiveness of an active shutter-glasses stereoscopic display (SD) and a passive polarised SD was evaluated in a live robot-teleoperation task and a simulated indirect-vision driving task in various terrains. Overall, participants completed their tasks significantly faster with the SDs in three-dimensional (3D) mode than with the SDs in the baseline 2D mode. They also navigated more accurately with the SDs in 3D mode. When the effectiveness of the two types of SDs was examined separately, results showed that the active shutter-glasses SD resulted in faster responses and task completion times than the passive polarised SD, though most of the differences failed to reach statistical significance. Perceived workload when interacting with the two SD systems did not differ significantly between the active versus passive display types or between the 3D and 2D modes of operation; however, participants reported more severe discomfort after interacting with the passive polarised SD.