A method of vertical and horizontal force estimation by using air-filled material and camera for soft physical human-robot interaction: fundamental experiments

A method of vertical and horizontal force estimation for soft physical human–robot interaction by using an air-filled material and a camera was proposed in this study. First, we considered hypotheses for vertical and horizontal force applied to the air-filled material. Second, the prototype of air-filled material and vision-based force-sensing device (AVFSD) was constructed. Based on the result of preliminary experiments, the relationships between force, pneumatic pressure, and contact surface displacement were formulated. The vertical and horizontal force could be estimated using the AVFSD with percentage errors of 3.6 and 5.8%, respectively, and the hypotheses were verified through the experiments.     

机器人触觉传感技术研发的历史现状与趋势

触觉是机器人实现与外部环境直接作用的必需媒介．相对其它机器人传感技术触觉传 感技术已明显落后．本文从总体上简要回顾触觉传感技术研发历程，分析指出其中的不足与 主要原因．在简述目前触觉传感技术研发的现状后，介绍分析机器人技术发展的新趋势及随 之而来的触觉传感技术发展趋势．对今后触觉传感技术的研发提出我们的见解．     

High-velocity walk-through programming for industrial applications

Traditionally, industrial robots are programmed by highly specialized workers that either directly write code in platform-specific languages, or use dedicated hardware (teach-pendant) to move the robot through the desired via-points. Unsurprisingly, the inherently complex and time-consuming nature of this task is one of the factors that are still preventing industrial manipulators from being massively adopted by companies that require a high degree of flexibility in order to cope with limited production volumes and rapidly changing product requirements. In this context, the introduction of sensor-based walk-through programming approaches represents the ideal solution as far as the need to reduce programming complexity and time is concerned. Nevertheless, the main shortcomings of these solutions typically consist in limited reachable velocities during the programming phase due to safety constraints and in relying on open robot controllers. To this regard, this paper proposes a control architecture for walk-through programming of industrial manipulators specifically designed in order to (i) reach high velocities while guaranteeing the operator’s safety; (ii) allow straightforward integration with a generic closed robotic controller. The proposed solution is extensively validated on an industrial manipulator.     

Deep learning in robotics: a review of recent research

Advances in deep learning over the last decade have led to a flurry of research in the application of deep artificial neural networks to robotic systems, with at least 30 papers published on the subject between 2014 and the present. This review discusses the applications, benefits, and limitations of deep learning vis-à-vis physical robotic systems, using contemporary research as exemplars. It is intended to communicate recent advances to the wider robotics community and inspire additional interest in and application of deep learning in robotics.     

Interaction forces beneath cuffs of physical assistant robots and their motion-based estimation

Most lower-limb physical assistant robots are fixed to wearers using cuffs. Hence, skin injuries beneath the cuffs are one of the major concerns of the users. A model that describes the relationship between the body posture and the interaction forces at the cuff was developed for use in assessing the risk of injury and improving user comfort. We measured the motion and interaction force beneath cuffs during the sitting and standing motions of subjects and a physical assistant robot which has been hardly reported thus far. Because of slippage and biomechanical motion, a traditional spring-damper model was found to be insufficient to describe the interaction forces associated with the measured motion of the cuffs. A parameter representing the motion or the knee joint angle was added to take into account these factors. Our model for estimation of the interaction forces using a spring, a damper, and the attitude of the lower leg fits the measured data especially well for the thigh cuff and is better than the traditional model. The applicability of this model was verified for several assist modes and wearers. The model was found to describe approximately 90% of the burden on the wearer, which reached a peak of approximately 60 N, the most hazardous condition. Having been validated for a commercial assistant robot, the model can be used to estimate the skin burdens beneath the cuffs without any force-sensitive elements.     

Designing LED lights for a robot to communicate gaze

ABSTRACT

Eye gaze is considered to be a particularly important non-verbal communication cue. Gaze research is also becoming a hot topic in human–robot interaction (HRI). However, research on social eye gaze for HRI focuses mainly on human-like robots. There remains a lack of methods for functional robots, which are constrained in appearance, to show gaze-like behavior. In this work, we investigate how we can implement gaze behavior in functional robots to assist humans in reading their intent. We explore design implications based on LED lights as we consider LEDs to be easily installed in most robots while not introducing features that are too human-like (to prevent users from having high expectations towards the robots). In this paper, we first developed a design interface that allows designers to freely test different parameter settings for an LED-based gaze display for a Roomba robot. We summarized design principles for well simulating LED-based gazes. Our suggested design is further evaluated by a large group of participants with regard to their perception and interpretation of the robot's behaviors. On the basis of the findings, we finally offer a set of design implications that can be beneficial to HRI and HCI researchers.     

Visual detection and tracking with UAVs,following a mobile object

ABSTRACT

Conception and development of an Unmanned Aerial Vehicle (UAV) capable of detecting, tracking and following a moving object with unknown dynamics is presented in this work, considering a human face as a case of study. Object detection is accomplished by a Haar cascade classifier. Once an object is detected, it is tracked with the help of a Kalman Filter (KF), and an estimation of the relative position with respect to the target is obtained. A linear controller is used to validate the proposed vision scheme and for regulating the aerial robot's position in order to keep a constant distance with respect to the mobile target, employing as well the extra available information from the embedded sensors. The proposed system was extensively tested in real-time experiments, through different conditions, using a commercial quadcopter connected via wireless to a ground station running under the Robot Operative System (ROS). The proposed overall strategy shows a good performance even under disadvantageous conditions as outdoor flight, being robust against illumination changes, image noise and the presence of other people in the scene.     

Towards physical interaction-based sequential mobility assistance using latent generative model of movement state

ABSTRACT

In this paper, we address sequential mobility assistance for daily elderly care through physical human–robot interaction. The goal of this work is to develop a robotic assistive system to provide physical support in daily life such as movement transition, e.g. sit-to-stand and walking. Using a mobile human support robotic platform, we propose an unsupervised learning-based approach to providing desirable physical support through an adaptive impedance parameter selection strategy according to the recognized user's movement state in an online manner. Using a latent generative model with a long short-term memory-based variational autoencoder, we first estimate the probability of the user's current movement state based on the sensory information in a low dimensional latent space. Then, the desired impedance parameters are selected adaptively according to the estimated movement state. One of the benefits of such an unsupervised learning approach is that no labeling is necessary in the training phase. Furthermore, our proposed framework is capable of detecting possible novel states such as falling over based on the obtained latent space. In order to demonstrate the proof of concept of our proposed approach, we present the experimental results of performance evaluations of online movement state recognition as well as novel movement detection.     

Natural human–robot musical interaction: understanding the music conductor gestures by using the WB-4 inertial measurement system

This paper presents an inertial measurement unit-based human gesture recognition system for a robot instrument player to understand the instructions dictated by an orchestra conductor and accordingly adapt its musical performance. It is an extension of our previous publications on natural human–robot musical interaction. With this system, the robot can understand the real-time variations in musical parameters dictated by the conductor’s movements, adding expression to its performance while being synchronized with all the other human partner musicians. The enhanced interaction ability would obviously lead to an improvement of the overall live performance, but also allow the partner musicians, as well as the conductor, to better appreciate a joint musical performance, thanks to the complete naturalness of the interaction.     

Effects of tactile cueing on concurrent performance of military and robotics tasks in a simulated multitasking environment

This study examined the concurrent performance of military gunnery, robotics control and communication tasks in a simulated environment. More specifically, the study investigated how aided target recognition (AiTR) capabilities (delivered either through tactile or tactile + visual cueing) for the gunnery task might benefit overall performance. Results showed that AiTR benefited not only the gunnery task, but also the concurrent robotics and communication tasks. The participants' spatial ability was found to be a good indicator of their gunnery and robotics task performance. However, when AiTR was available to assist their gunnery task, those participants of lower spatial ability were able to perform their robotics tasks as well as those of higher spatial ability. Finally, participants' workload assessment was significantly higher when they teleoperated (i.e. remotely operated) a robot and when their gunnery task was unassisted. These results will further understanding of multitasking performance in military tasking environments. These results will also facilitate the implementation of robots in military settings and will provide useful data to military system designs.     

Evaluation of diagnostician user interface aspects in a virtual reality-based tele-ultrasonography simulation

ABSTRACT

Ultrasonography (USG) is a common medical examination that can be performed remotely and that highly benefits from robotics. In this paper, we evaluate a novel interface for a telediagnosis system that features haptic feedback and a 2D/3D visualization of the remote site. A Virtual Environment (VE) representing the patient site was used for the validation to stress the interaction capabilities of the interface and to decouple expert's interface performance from the effects of the whole teleoperation loop of a telediagnosis system. The interface evaluation measures include the accuracy that doctors achieve when positioning the interface's end-effector in the VE and the success of experts to perform tasks related to cardiac USG that require force feedback. Twelve experienced sonographers performed four experiments in which visualization modality and VE navigation technique varied. Given the limitations of an evaluation in simulated settings, both quantitative results and experts' opinions suggest that the interface is suitable for integration in tele-USG systems. After a positive evaluation of latencies and rendered forces, we show how navigation condition influences the accuracy of the end-effector positioning as well as the covered distance and the elapsed time to accomplish the tasks. Similarly, we highlight the effect of visualization on accuracy.     

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.     

Effects of automation and task load on task switching during human supervision of multiple semi-autonomous robots in a dynamic environment

The present study assessed the impact of task load and level of automation (LOA) on task switching in participants supervising a team of four or eight semi-autonomous robots in a simulated ‘capture the flag’ game. Participants were faster to perform the same task than when they chose to switch between different task actions. They also took longer to switch between different tasks when supervising the robots at a high compared to a low LOA. Task load, as manipulated by the number of robots to be supervised, did not influence switch costs. The results suggest that the design of future unmanned vehicle (UV) systems should take into account not simply how many UVs an operator can supervise, but also the impact of LOA and task operations on task switching during supervision of multiple UVs.

The findings of this study are relevant for the ergonomics practice of UV systems. This research extends the cognitive theory of task switching to inform the design of UV systems and results show that switching between UVs is an important factor to consider.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

Trajectory tracking control of a 6-DOF hydraulic parallel robot manipulator with uncertain load disturbances

This study addresses the trajectory tracking control of a 6-DOF (degrees of freedom) hydraulic parallel robot manipulator with uncertain load disturbances. As load disturbances are the main external disturbances of the parallel robot manipulators and have a significant impact on system tracking performance, many researchers have been devoted to synthesize advanced control methods for improving the system robustness under the assumption that load disturbances are bounded. However, load disturbances are uncertain and vary in a large range in real situation happening in most hydraulic parallel robot manipulators, which is opposed to the assumption. In this paper, the load disturbances are directly measured by force sensors. Then a sliding mode control with discontinuous projection-based adaptation laws is proposed to improve the tracking performance of the parallel robot manipulator. Simulations and experiments with typical desired trajectory are presented, and the results show that good tracking performance is achieved in the presence of uncertain load disturbances.     

The benefit of being physically present: A survey of experimental works comparing copresent robots,telepresent robots and virtual agents

The effects of physical embodiment and physical presence were explored through a survey of 33 experimental works comparing how people interacted with physical robots and virtual agents. A qualitative assessment of the direction of quantitative effects demonstrated that robots were more persuasive and perceived more positively when physically present in a user׳s environment than when digitally-displayed on a screen either as a video feed of the same robot or as a virtual character analog; robots also led to better user performance when they were collocated as opposed to shown via video on a screen. However, participants did not respond differently to physical robots and virtual agents when both were displayed digitally on a screen – suggesting that physical presence, rather than physical embodiment, characterizes people׳s responses to social robots. Implications for understanding psychological response to physical and virtual agents and for methodological design are discussed.     

Modeling the impact of interaction on pedestrian group motion

Mobile social robots aimed at interacting with and assisting humans in pedestrian areas need to understand the dynamics of pedestrian social interaction. In this work, we investigate the effect of interaction on pedestrian group motion by defining three motion models to represent (1) interpersonal-distance, (2) relative orientation and (3) absolute difference of velocities; and model them using a dataset of 12000+ pedestrian trajectories recorded in uncontrolled settings. Our contributions include: (i) Demonstrating that interaction has a prominent effect on the empirical distributions of the proposed joint motion attributes, where increasing levels of interaction lead to more regular behavior (ii) Developing analytic motion models of such distributions and reflect the effect of interaction on model parameters (iii) Detecting the social groups in a crowd with almost perfect accuracy utilizing the proposed models, despite the constant flow direction in the environment which causes unrelated pedestrians to move in a correlated way, and thus makes group recognition more difficult (iv) Estimating the level of intensity with considerable rates utilizing the proposed models     

信息触觉表达技术的研究现状与应用

触觉表达是一种新兴的人机交互模式和信息传递方式.首先介绍了触觉表达技术的研究背景,讨论了触觉表达装置的特点和种类,接着分类介绍了国内外触觉表达装置的研究历史和现状,然后分析了当前信息的触觉表达技术研究中存在的问题,最后讨论了触觉表达装置的应用前景和发展趋势.     

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.