Section: New Results

Interactions between walkers

Participants : Anne-Hélène Olivier, Armel Crétual, Julien Bruneau, Richard Kulpa, Sean Lynch, Julien Pettré.

Interaction between people, and especially local interaction between walkers, is a main research topic of MimeTIC. We propose experimental approaches using both real and virtual environments. This year, we developped new experiments in our immersive platform. First, we investigated obstacle avoidance behavior during real walking in a large immersive projection setup [22] . We analyze the walking behavior of users when avoiding real and virtual static obstacles. Indeed, CAVE-like immersive projection environments enable users to see both virtual and real objects, including the user’s own body. With recent advances in VR technologies it becomes possible to build large-scale tracked immersive projection environments, which enable users to control their position in a large region of interest by real walking. In such environments virtual and real objects as well as multiple users or avatars may coexist in the same interaction space. Hence, it becomes important to gain an understanding of how the user’s behavior is affected by the differences in perception and affordances of such real and virtual obstacles. We consider both anthropomorphic and inanimate objects, each having his virtual and real counterpart. The results showed that users exhibit different locomotion behaviors in the presence of real and virtual obstacles, and in the presence of anthropomorphic and inanimate objects. Precisely, the results showed a decrease of walking speed as well as an increase of the clearance distance (i. e., the minimal distance between the walker and the obstacle) when facing virtual obstacles compared to real ones. Moreover, users act differently due to their perception of the obstacle: users keep more distance when the obstacle is anthropomorphic compared to an inanimate object and when the orientation of anthropomorphic obstacle is from the profile compared to a front position. However, although we observed differences in collision avoidance behavior between real and virtual obstacles, which indicate biases of natural locomotion introduced by the setup, their magnitude seem lower compared to typical results found in HMD environments.This suggests that although the user’s behavior in mixed environments varies depending on the nature of the stimulus, the user’s locomotion behavior and the management of his/her interaction space is comparable with the ones in real life. Considering these findings, our results open promising vistas for using large CAVE-like setups for socio-physical experiments, in particular in the fields of locomotion and behavioral dynamics.

Second, we studied interactions between an individual and a crowd [7] . When avoiding a group, a walker has two possibilities: either he goes through it or around it. Going through very dense group or around huge one would not seem natural and could break any sense of presence in a virtual environment. The aim of this work was to enable crowd simulators to correctly handle such situations. To this end, we need understanding how real humans decide to go through or around groups. As a first hypothesis, we apply the Principle of Minimum Energy (PME) on different group sizes and density. According to it, a walker should go around small and dense groups while he should go through large and sparse groups. We quantified decision thresholds. However, PME left some inconclusive situations for which the two solutions paths have similar energetic cost. In a second part, we proposed an experiment to corroborate PME decisions thresholds with real observations. We proposed using Virtual Reality to enable accurately controlling experimental factors. We considered as well the role of secondary factors in inconclusive situations. We showed the influence of the group appearance and direction of relative motion in the decision process. Finally, we draw some guidelines to integrate our conclusions to existing crowd simulators and demonstrate that spectators can perceive some improvement in the crowd animation.

This year, we also developed new experiments in real conditions by considering the interaction between a walker and a moving robot. This worked was performed in collaboration with Philippe Souères and Christian Vassallo (LAAS, Toulouse). The development of Robotics accelerated these recent years, it is clear that robots and humans will share the same environment in a near future. In this context, understanding local interactions between humans and robots during locomotion tasks is important to steer robots among humans in a safe manner. Our work is a first step in this direction. Our goal is to describe how, during locomotion, humans avoid collision with a moving robot. We study collision avoidance between participants and a non-reactive robot (we wanted to avoid the effect of a complex loop by a robot reacting to participants’ motion). Our objective is to determine whether the main characteristics of such interaction preserve the ones previously observed: accurate estimation of collision risk, anticipated and efficient adaptations. We observed that collision avoidance between a human and a robot has similarities with human-human interactions (estimation of collision risk, anticipation) but also leads to major differences. Humans preferentially give way to the robot, even if this choice is not optimal with regard to motion adaptation to avoid the collision. We proposed to interpret this behavior based on the notion of perceived danger and safety. Given the difficulty to understand how a robot behaves, and the lack of experience of interactions with the robot, humans apply a conservative avoidance strategy and prefer giving way to the robot. However, it is important to note that human participants succeed in perceiving the motion of the robot (anticipation was observed, no aberrant reaction occurred). One main conclusion is that, if we control robots to move like humans, we have a risk facing unexpected situations where robot compensates and cancels humans adaptations to the robot. A robot programmed to be cooperative could be perceived as hostile. The conclusion of this study opens paths for future research. A first direction is to better understand the possible effect of this notion of danger during interactions. We believe that this notion is of even higher importance when studying interactions with vehicles: a risk of collision with a fast vehicle obviously raises higher danger. A second direction is about the design of safe robots moving among human walkers. How the robot should adapt to others? Should it be collaborative with the risk of compensating human avoidance strategies? Should it be passive? We believe that robots should first be equipped with the ability to early detect humans avoidance strategy and adapt to it. In the near future, we want to continue our study of interactions between a robot and a human. In a first step, we plan to equip the robot with collision avoidance system which imitates real human strategies, and investigate how participants adapt to this new situation in comparison with a passive robot.

Finally, Sean Dean Lynch has been recruited as a PhD student since september 2015. This thesis concerns the visual perception of human motion during interactions in locmotor tasks. From the visual perception of someone’s motion, we are able to predict the future course of this motion, interpret and anticipate his/her intentions and adapt our own motion to allow interactions. The main objective of the thesis is to identify the underlying perceptual mechanisms, i.e., the human motion cues which are necessary for an accurate understanding of others’ intentions. It would allow to make significant progress in the understanding of human social behaviors. To reach these objectives, the thesis will be based on an experimental approach in virtual reality.