An athletic approach to studying perception-action integration: Does sport-specific training, and the impact of injury, influence how individuals visually guide navigation?

The objective of this thesis was to investigate perception-action integration capabilities of individuals during a choice navigation task. This task assessed navigation strategies in open space while individuals avoided colliding with two vertical obstacles that created a body-scaled, horizontal gap, at three varying obstacle distances from the starting location (3m, 5m, 7m). The two studies completed in this thesis employed the same paradigm to assess the hypothesized group differences. Gaze behaviours and kinematics of navigation strategies were compared between: 1) athletes specifically trained in navigating in open space versus non-athletes; and 2) athletes with post-concussion syndrome (PCS) versus non-concussed, specifically trained athletes. Specifically trained athletes have been identified as demonstrating more successful perception-action integration in discrete motor tasks related to their sport (Mann et al., 2007; Vickers, 2007). However, whether these abilities translate to the continuous motor task of obstacle avoidance in open space was unknown. The purpose of Study 1 was to identify the influence of sport-specific training on navigating in open space (i.e. navigational strategies of large field sport athletes) compared to age-matched, non-athletes. It was hypothesized that specifically-trained athletes would demonstrate fewer, longer fixations, suggesting a more successful perception-action integration strategy (as defined by Mann et al., 2007), and would employ more sport-specific navigation strategies than non-athletes by maintaining their straight trajectory toward the goal (Fajen & Warren, 2003). Athletes were found to make fewer, longer fixations than non-athletes. However, no differences were observed between navigation strategies of the two groups, nor were any kinematic measures found to differ between groups. It can be concluded that athletes and non-athletes differentially obtain visual information to perform the same actions, suggesting that athletes and non-athletes differentially perform perception-action integration when navigating in open space. Future studies are required to identify sport-specific nuances of navigation (moving obstacles, running) to better identify athletic-related navigation strategies. Although athletic training can enhance perception-action integration strategies, sport-related injuries can hinder this process. Following a concussion, individuals experience deficits of perception-action integration that persist well beyond 30 days of recovery, post-concussion (Baker and Cinelli, 2014; Slobounov et al., 2006). These perception-action integration deficits may also exist in individual with postconcussion syndrome (PCS). The purpose of the Study 2 was to identify whether perception-action integration deficits persist with the persistent physical symptoms of concussion characteristic of PCS. The current study revealed that athletes with PCS did not differ from non-concussed athletes on any measure of visual fixation strategy, nor were they found to differ on any kinematic measure assessed. These findings suggest that in the context of the current paradigm, athletes with PCS have no perception-action integration deficit. In that, athletes with PCS may have adapted perception-action integration strategies to navigate with equal efficiency as a specifically-trained group of athletes or that the paradigm was not sensitive enough to identify these differences. Such findings suggest that more research is required to assess what, if any, perception-action integration deficits persist with persisting physical symptoms of PCS to better benefit rehabilitative procedures and outcomes for these individuals. Together, these studies add to what was previously known about perception-action integration, as it relates to navigation. Both studies assessed perception-action integration in unique populations that add to understanding of behavioural dynamics in the sport setting. Study 1 builds on a line of research assessing affordance theory and behavioural dynamics in sport (Fajen, Riley, & Turvey, 2008). The findings of this study suggest that although navigation strategies did not differ between specifically trained athletes and non-athletes, visual search strategies employed in task did. Such findings add to the understanding that sport-specific training influences perception-action integration, through our understanding of how athletes obtain visual information to perform actions. This thesis did not identify perception-action integration deficits in athletes with PCS. These findings suggest that the individuals in the present study likely adapted to their injury as they demonstrated equal ability in gaze and navigation strategies to specifically-trained athletes. As such, further research is required to assess the cognitive, motor, and sensory-motor deficits that may persist with the persisting physical symptoms of PCS. As individuals with PCS do not demonstrate similar visuomotor integration deficits as individuals with acute concussions (Baker & Cinelli, 2014), such individuals must be assessed and researched as a separate population

Embodied Evolution in Collective Robotics: A Review

This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives -- namely, embodied evolution. It provides a definition of embodied evolution as well as a thorough description of the underlying concepts and mechanisms. The paper also presents a comprehensive summary of research published in the field since its inception (1999-2017), providing various perspectives to identify the major trends. In particular, we identify a shift from considering embodied evolution as a parallel search method within small robot collectives (fewer than 10 robots) to embodied evolution as an on-line distributed learning method for designing collective behaviours in swarm-like collectives. The paper concludes with a discussion of applications and open questions, providing a milestone for past and an inspiration for future research.Comment: 23 pages, 1 figure, 1 tabl

Analysis-by-synthesis: Pedestrian tracking with crowd simulation models in a multi-camera video network

For tracking systems consisting of multiple cameras with overlapping field-of-views, homography-based approaches are widely adopted to significantly reduce occlusions among pedestrians by sharing information among multiple views. However, in these approaches, the usage of information under real-world coordinates is only at a preliminary level. Therefore, in this paper, a multi-camera tracking system with integrated crowd simulation is proposed in order to explore the possibility to make homography information more helpful. Two crowd simulators with different simulation strategies are used to investigate the influence of the simulation strategy on the final tracking performance. The performance is evaluated by multiple object tracking precision and accuracy (MOTP and MOTA) metrics, for all the camera views and the results obtained under real-world coordinates. The experimental results demonstrate that crowd simulators boost the tracking performance significantly, especially for crowded scenes with higher density. In addition, a more realistic simulation strategy helps to further improve the overall tracking result

Decentralized Connectivity-Preserving Deployment of Large-Scale Robot Swarms

We present a decentralized and scalable approach for deployment of a robot swarm. Our approach tackles scenarios in which the swarm must reach multiple spatially distributed targets, and enforce the constraint that the robot network cannot be split. The basic idea behind our work is to construct a logical tree topology over the physical network formed by the robots. The logical tree acts as a backbone used by robots to enforce connectivity constraints. We study and compare two algorithms to form the logical tree: outwards and inwards. These algorithms differ in the order in which the robots join the tree: the outwards algorithm starts at the tree root and grows towards the targets, while the inwards algorithm proceeds in the opposite manner. Both algorithms perform periodic reconfiguration, to prevent suboptimal topologies from halting the growth of the tree. Our contributions are (i) The formulation of the two algorithms; (ii) A comparison of the algorithms in extensive physics-based simulations; (iii) A validation of our findings through real-robot experiments.Comment: 8 pages, 8 figures, submitted to IROS 201