Effect of leader placement on robotic swarm control

Human control of a robotic swarm entails selecting a few in-fluential leaders who can steer the collective efficiently and robustly. However, a clear measure of influence with respect to leader position is not adequately studied. Studies with animal systems have shown that leaders who exert strong couplings may be located in front, where they provide energy benefits, or in the middle, where they can be seen by a larger section of the group. In this paper, we systematically vary number of leaders and leader positions in simulated robotic swarms of two different sizes, and assess their effect on steering effectiveness and energy expenditure. In particular, we analyze the effect of placing leaders in the front, middle, and periphery, on the time to converge and lateral acceleration of a swarm of robotic agents as it performs a single turn to reach the desired goal direction. Our results show that swarms with leaders in the middle and periphery take less time to converge than swarms with leaders in the front, while the lateral acceleration between the three placement strategies is not different. We also find that the time to converge towards the goal direction reduces with the increase in percentage of leaders in the swarm, although this value decays slowly beyond the percentage of leaders at 30%. As the swarm size is increased, we find that the leaders in the periphery become less effective in reducing the time to converge. Finally, closer analysis of leader placement and coverage reveals that front leaders within the swarm tend to expand their coverage and move towards the center as the maneuver is performed. Results from this study are expected to inform leader placement strategies towards more effective human swarm interaction systems

Measurement and Analysis of Cognitive Load Associated with Moving Object Classification in Underwater Environments

Visual analysis in field science experiments often involves classifying objects on experimental images and videos. In this context, developing a reliable and independently validated estimate of mental workload during object classification can enable cognitively responsive task allocation. The goal of this study is to quantify the cognitive load perceived by humans from electroencephalography (EEG) data during an underwater object classification task that was inspired from citizen science studies. During the task, participants were asked to identify one of three possible invasive fish species in short videos of a virtual underwater environment. The virtual environment was modeled to vary fish behavior and environmental factors that are known to be critical in classification. A contextually-relevant secondary task was designed to provide independent validation of cognitive load measures. Several established measures of cognitive load were compared across different weightings on the scalp positions, and the measure that strongly associated with reaction time and a secondary task accuracy was selected for further analysis. Our results show that cognitive load calculated using the difference in power of alpha frequencies best correlates with reaction time and secondary task accuracy. When fit to the environmental factors, cognitive load calculated using this approach was high when the environment was turbid and the fish moved at high speeds. Results from this study have applications in cognitively-responsive human–computer interaction and in developing shared control strategies in human–robot interaction.</p

Group coordination was always high.

<p>The polarization of zebrafish was not significantly different between conditions with the robot moving at varying speeds (, , , and ). Control conditions (No robot and Fixed) are shown for reference. Error bars represent standard error mean.</p

Robotic fish used in our experiments.

<p>The color pattern, aspect ratio, and shape of the caudal fin of the mobile robotic fish used in our experiments matched that of a zebrafish.</p

Group speed relative to the robot varied with robot speed.

<p>The relative speed of zebrafish was significantly different between conditions with the robot moving at varying speeds (, , , and ). Control conditions (No robot and Fixed) are shown for reference. Error bars represent standard error mean.</p

Group cohesion changed significantly with robot speed.

<p>Average nearest-neighbor distance between zebrafish as the robot moved at increasing speeds of , , and corresponding to a tail-beat frequency of , , , and respectively. Control conditions (No robot and Fixed) are shown for reference. Error bars represent standard error mean.</p

A summary of the experimental conditions.

<p>We considered tail-beat frequencies of , , , and corresponding to swimming speeds of , , , and . To control for the tail-beating movement and the presence of the robot, we conducted tests with the robot anchored to preset locations in the tank and without the robot.</p

Collective Response of Zebrafish Shoals to a Free-Swimming Robotic Fish

<div><p>In this work, we explore the feasibility of regulating the collective behavior of zebrafish with a free-swimming robotic fish. The visual cues elicited by the robot are inspired by salient features of attraction in zebrafish and include enhanced coloration, aspect ratio of a fertile female, and carangiform/subcarangiform locomotion. The robot is autonomously controlled with an online multi-target tracking system and swims in circular trajectories in the presence of groups of zebrafish. We investigate the collective response of zebrafish to changes in robot speed, achieved by varying its tail-beat frequency. Our results show that the speed of the robot is a determinant of group cohesion, quantified through zebrafish nearest-neighbor distance, which increases with the speed of the robot until it reaches . We also find that the presence of the robot causes a significant decrease in the group speed, which is not accompanied by an increase in the freezing response of the subjects. Findings of this study are expected to inform the design of experimental protocols that leverage the use of robots to study the zebrafish animal model.</p></div

Schematic of the experimental setup.

<p>The experimental apparatus consisted of a square shallow tank with overhead ultraviolet lighting and camera for real-time tracking.</p

Supplementary document from Drawing power of virtual crowds

Supplementary document with additional figures, analyses, and recruitment flyer imag