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

Fast, Autonomous Flight in GPS-Denied and Cluttered Environments

One of the most challenging tasks for a flying robot is to autonomously navigate between target locations quickly and reliably while avoiding obstacles in its path, and with little to no a-priori knowledge of the operating environment. This challenge is addressed in the present paper. We describe the system design and software architecture of our proposed solution, and showcase how all the distinct components can be integrated to enable smooth robot operation. We provide critical insight on hardware and software component selection and development, and present results from extensive experimental testing in real-world warehouse environments. Experimental testing reveals that our proposed solution can deliver fast and robust aerial robot autonomous navigation in cluttered, GPS-denied environments.Comment: Pre-peer reviewed version of the article accepted in Journal of Field Robotic

A layered fuzzy logic controller for nonholonomic car-like robot

A system for real time navigation of a nonholonomic car-like robot in a dynamic environment consists of two layers is described: a Sugeno-type fuzzy motion planner; and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including right and left views to identify the next step to the goal. A Sugeno-type fuzzy motion planner of four inputs one output is introduced to give a clear direction to the robot controller. The second stage is a modified proportional navigation based fuzzy controller based on the proportional navigation guidance law and able to optimize the robot's behavior in real time, i.e. to avoid stationary and moving obstacles in its local environment obeying kinematics constraints. The system has an intelligent combination of two behaviors to cope with obstacle avoidance as well as approaching a target using a proportional navigation path. The system was simulated and tested on different environments with various obstacle distributions. The simulation reveals that the system gives good results for various simple environments

Aerial navigation in obstructed environments with embedded nonlinear model predictive control

We propose a methodology for autonomous aerial navigation and obstacle avoidance of micro aerial vehicles (MAV) using nonlinear model predictive control (NMPC) and we demonstrate its effectiveness with laboratory experiments. The proposed methodology can accommodate obstacles of arbitrary, potentially non-convex, geometry. The NMPC problem is solved using PANOC: a fast numerical optimization method which is completely matrix-free, is not sensitive to ill conditioning, involves only simple algebraic operations and is suitable for embedded NMPC. A C89 implementation of PANOC solves the NMPC problem at a rate of 20Hz on board a lab-scale MAV. The MAV performs smooth maneuvers moving around an obstacle. For increased autonomy, we propose a simple method to compensate for the reduction of thrust over time, which comes from the depletion of the MAV's battery, by estimating the thrust constant

Navite: A Neural Network System For Sensory-Based Robot Navigation

A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.Defense Advanced Research Projects Agency (AFOSR 90-0083); Office of Naval Research (N00014-92-J-l309); Consejo Nacional de Ciencia y Tecnología (63l462