How do walkers behave when crossing the way of a mobile robot that replicates human interaction rules?

A Literature Review on Safety Perception and Trust during Human-Robot Interaction with Autonomous Mobile Robots That Apply to Industrial Environments

Occupational ApplicationsAutonomous mobile robots are used in manufacturing and warehousing industries, to transport material across the facility and deliver parts to work cells. Human workers might encounter or interact with these robots in aisle ways or at their workstation. It is important to consider factors that impact worker safety and trust when implementing autonomous mobile robots in the workplace. This paper reviews prior research that aims to improve the safety of human-robot interaction with autonomous mobile robots and identifies needs for future research. Researchers used a variety of questionnaires and behavioral assessment methods to measure perceived safety. Factors such as robot appearance, approach speed, and approach direction, significantly affect perceived safety. Additionally, projection of signals on the floor, turn signals, and haptic communication devices, can improve the predictability and overall safety of robot navigation.

Spontaneous gait phase synchronization of human to a wheeled mobile robot with replicating gait-induced upper body oscillating motion

Synchronization between humans is often observed in our daily lives, for example in breathing, in hand clapping in crowds, and in walking. It has been reported that pedestrian gait synchronization maximizes walking flow efficiency. As increasingly more mobile robots are being developed for practical use, it is important to consider how robots may impact pedestrian flows. While there is research on synchronization phenomena between humans and robots, gait synchronization between humans and robots has yet to be studied, particularly synchronization occurring with wheeled humanoid robots while moving. In this paper, we investigated the gait phase synchronization between humans and a wheeled mobile humanoid robot, which moved its upper body in three distinct types of motion patterns: (1) no-motion, (2) arm-swinging (as is common for typical mobile humanoids), and (3) arms-swinging in addition to periodic vertical-oscillation similar to the human upper body movement while walking. Rayleigh test was performed on the distribution of the obtained gait phase differences under each condition and a significant distributional bias was confirmed when participants were walking with the robot that performed both arm-swinging and vertical-oscillation of the upper body. These results suggest that humans can spontaneously synchronize their gaits with wheeled robots that utilize upper body oscillating. These findings can be important for the design of robot-integrated urban transportation systems, such as train stations and airports, where both humans and robots are mobile and a highly efficient flow is required.

From HRI to CRI: Crowd Robot Interaction—Understanding the Effect of Robots on Crowd Motion

How does the presence of a robot affect pedestrians and crowd dynamics, and does this influence vary across robot type? In this paper, we took the first step towards answering this question by performing a crowd-robot gate-crossing experiment. The study involved 28 participants and two distinct robot representatives: A smart wheelchair and a Pepper humanoid robot. Collected data includes: video recordings; robot and participant trajectories; and participants’ responses to post-interaction questionnaires. Quantitative analysis on the trajectories suggests the robot affects crowd dynamics in terms of trajectory regularity and interaction complexity. Qualitative results indicate that pedestrians tend to be more conservative and follow “social rules” while passing a wheelchair compared to a humanoid robot. These insights can be used to design a social navigation strategy that allows more natural interaction by considering the robot effect on the crowd dynamics.

Back-off

Standstill behavior by a robot is deemed to be ineffective and inefficient to convey a robot’s intention to yield priority to another party in spatial interaction. Instead, robots could convey their intention and thus their next action via motion. We developed a back-off (BO) movement to communicate the intention of yielding priority to pedestrians at bottlenecks. To evaluate human sensory perception and subjective legibility, the BO is compared to three other motion strategies in a video study with 167 interviewees at the university and public spaces, where it excels regarding legibility. Implemented in a real encounter, objective motion behavior of 78 participants as a reaction to a stop-and-wait strategy, and two versions of BO (short and long), shows an improvement of the pedestrians’ efficiency in the second encounter with the robot’s short BO version compared to the stop strategy. Eventually, in the third encounter with all motion strategies, interaction causes only a small time consumption still required by the cognitive process of perceiving an object in the visual field. Hence, the design of kinematic parameters, BO path and time, exhibits the potential to increase the fluency of an interaction with robots at bottlenecks.

When Agents Become Partners: A Review of the Role the Implicit Plays in the Interaction with Artificial Social Agents

The way we interact with computers has significantly changed over recent decades. However, interaction with computers still falls behind human to human interaction in terms of seamlessness, effortlessness, and satisfaction. We argue that simultaneously using verbal, nonverbal, explicit, implicit, intentional, and unintentional communication channels addresses these three aspects of the interaction process. To better understand what has been done in the field of Human Computer Interaction (HCI) in terms of incorporating the type channels mentioned above, we reviewed the literature on implicit nonverbal interaction with a specific emphasis on the interaction between humans on the one side, and robot and virtual humans on the other side. These Artificial Social Agents (ASA) are increasingly used as advanced tools for solving not only physical but also social tasks. In the literature review, we identify domains of interaction between humans and artificial social agents that have shown exponential growth over the years. The review highlights the value of incorporating implicit interaction capabilities in Human Agent Interaction (HAI) which we believe will lead to satisfying human and artificial social agent team performance. We conclude the article by presenting a case study of a system that harnesses subtle nonverbal, implicit interaction to increase the state of relaxation in users. This “Virtual Human Breathing Relaxation System” works on the principle of physiological synchronisation between a human and a virtual, computer-generated human. The active entrainment concept behind the relaxation system is generic and can be applied to other human agent interaction domains of implicit physiology-based interaction.

Influence of path curvature on collision avoidance behaviour between two walkers

Navigating crowded community spaces requires interactions with pedestrians that follow rectilinear and curvilinear trajectories. In the case of rectilinear trajectories, it has been shown that the perceived action opportunities of the walkers might be afforded based on a future distance of closest approach. However, little is known about collision avoidance behaviours when avoiding walkers that follow curvilinear trajectories. Twenty-two participants were immersed in a virtual environment and avoided a virtual human (VH) that followed either a rectilinear path or a curvilinear path with a 5 m or 10 m radius curve at various distances of closest approach. Compared to a rectilinear path (control condition), the curvilinear path with a 5 m radius yielded more collisions when the VH approached from behind the participant and more inversions when the VH approached from in-front. During each trial, the evolution of the future distance of closest approach showed similarities between rectilinear paths and curvilinear paths with a 10 m radius curve. Overall, with few collisions and few inversions of crossing order, we can conclude that participants were capable of predicting future distance of closest approach of virtual walkers that followed curvilinear trajectories. The task was solved with similar avoidance adaptations to those observed for rectilinear interactions. These findings should inform future endeavors to further understand collision avoidance strategies and the role of-for example-non-constant velocities.

Limb movements of another pedestrian affect crossing distance but not path planning during virtual over ground circumvention

Circumventing another pedestrian is a frequent daily activity. The literature has provided a better understanding about anticipatory locomotor adjustments based on global (whole body) movement, but how local limb movements of another pedestrian affect one's circumvention is not well known. The purpose of this study was to understand how local limb movements of another pedestrian affect the planning and execution to circumvent them. Ten healthy young adults (24.5 ± 3.0 years) were immersed in a virtual environment representing a shopping mall. Participants walked to a shop located directly in front of them while circumventing a virtual agent which, when present, approached from straight ahead with one of four different locomotor patterns: 1-Normal locomotor movements; 2- No arm movements; 3- No leg movements; 4- No arm and leg movements (gliding to them). Circumvention trajectory, minimum clearance and coordination of head and trunk rotations along with center of mass lateral displacement were examined. Nonparametric Analysis of Longitudinal Data was used to compare variables across the different conditions. Minimum clearance was smaller for normal locomotor movements compared to all other conditions, but coordination of body movements and onset of circumvention trajectory deviations remained unchanged. These results suggest that global body movement is sufficient to plan circumvention trajectories in a predictable avoidance task, but clearance safety margins are influenced by the local limb movements of another pedestrian.

Walking pattern efficiency during collective load transport

BACKGROUND

While the locomotor behavior of humans walking alone has been extensively studied, the locomotor behavior of humans transporting a load collectively is very poorly documented in the biomechanics literature. Yet, collective transport could find potential developments in other domains such as rehabilitation and robotics.

RESEARCH QUESTION

If collective load transport is made economically one could expect that the center of mass of the ensemble formed by several individuals and the load they carry has the same pendulum-like behavior as a single individual walking alone. The main objective of our study was to assess to what extent this is the case.

METHODS

We recorded the 3D kinematics of movement of the body segments of ten dyads formed by two persons carrying a load together in three successive trials. The individuals carried the load, side by side, along a 13 m straight trajectory. Then, the recovery rate of the center of mass of the ensemble formed by the two individuals and the load they carry (i.e. the rate of transfer between potential and kinetic energy) was computed.

RESULTS

The values of recovery rate were similar to those found in the literature for individuals walking alone, showing that the external energetic exchanges occurring during collective transport are as efficient as those occurring in single gait. The recovery rate also increased in successive trials, suggesting an improvement of the performance with familiarization.

SIGNIFICANCE

Our results demonstrate the ability of humans to collaborate efficiently for carrying a load. The values of recovery rate we found could be used as a benchmark for the control of collaborative robots.