In this paper, we present a strategy for organizing swarms of unmanned vehicles into a formation by utilizing artificial potential fields that were generated from normal and sigmoid functions. These functions construct the surface on which swarm members travel, controlling the overall swarm geometry and the individual member spacing. Nonlinear limiting functions are defined to provide tighter swarm control by modifying and adjusting a set of control variables that force the swarm to behave according to set constraints, formation, and member spacing. The artificial potential functions and limiting functions are combined to control swarm formation, orientation, and swarm movement as a whole. Parameters are chosen based on desired formation and user-defined constraints. This approach is computationally efficient and scales well to different swarm sizes, to heterogeneous systems, and to both centralized and decentralized swarm models. Simulation results are presented for a swarm of 10 and 40 robots that follow circle, ellipse, and wedge formations. Experimental results are included to demonstrate the applicability of the approach on a swarm of four custom-built unmanned ground vehicles (UGVs).
Vehicle Technology Directorate, ARLApproved for public release; distribution unlimited. ii REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing the burden, ARL-TR-4800 SPONSOR/MONITOR'S ACRONYM(S) 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) SPONSOR/MONITOR'S REPORT NUMBER(S) DISTRIBUTION/AVAILABILITY STATEMENTApproved for public release; distribution unlimited. SUPPLEMENTARY NOTES ABSTRACTIn theory, autonomous robotic swarms can be used for critical Army tasks (i.e., accompanying convoys); however, the Soldier controlling the swarm must be able to monitor swarm status and correct actions, especially in disrupted or degraded conditions. For this two-year Director's Research Initiative (DRI), we designed metacognition algorithms and Soldier-swarm display concepts to allow Soldiers to efficiently interact with a robotic swarm participating in a representative convoy mission. We used a potential field approach for swarm control because it scales easily to large heterogeneous swarms and allows users to dynamically alter swarm behavior by adjusting field parameters. The Soldier-swarm interface displayed swarm and convoy geospatial position; swarm health and communication; and convoy status information, using visual, auditory, and tactile combinations. We measured swarm metacognition by determining the proportion of time the simulated swarm could maintain a specific orbital ring around the convoy over six terrains in 13-min scenarios. We tested interface effectiveness in a laboratory study using 16 male Marines (volunteers) with a mean age of 19 years. The metacognition results showed that the swarm could maintain the pre-defined dispersion more than 85% of the time in each terrain. Using multimodal displays, Soldier workload decreased and performance increased (i.e., response time reduced).
Abstract-In theory, autonomous robotic swarms can be used for critical Army tasks, including accompanying vehicle convoys to provide security and enhance situational awareness. However, the Soldier providing swarm supervisory control must be able to correct swarm actions, especially in disrupted or degraded conditions. Dynamic map displays are visual interfaces that can be useful for swarm supervisory control tasks, because they can show the spatial positions of objects of interest (e.g., people, robots, swarm members, and vehicles), at different locations (e.g., on roads and intersections), while allowing user commands as well as world changes, often in real time. In this study, multimodal speech and touch controls were designed for a U.S. Army Research Laboratory dynamic map display to allow users to provide supervisory control of a simulated robotic swarm. This experiment explored the use of sequential multimodal touch and speech commands for placement of swarm-related map objects at different map locations. The criterion variable was temporal binding, the time between the onset of each command in the sequence, relative to the system's ability to fuse the two sequential commands into a unitary response. User preference of modality for the first command was also measured. These concepts were tested in a laboratory study using 12 male Marine volunteers with a mean age of 19 years. Results indicated significant differences in temporal binding for different map objects and map locations. Additionally, nine out of 12 Marines used speech commands approximately 75% or more of the time, while the remaining three Marines used touch commands first approximately 75% or more of the time. Temporal binding was significantly shorter for touch-first than for speech-first commands.Suggestions for future research and future applications to robotic command and control systems are described.
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