Name
Abstract | ||
|---|---|---|
Typical visualizations of robot swarms (greater than 50 entities) display each individual entity; however, it is immensely difficult to maintain accurate position information for each member in real-world situations with limited communications. Generally, it will be difficult for humans to maintain an awareness of all individual entities. Further, the swarm's tasks may impact the desired visualization. Thus, an open question is how best to visualize a swarm given various swarm tasks. This paper presents a heuristic evaluation that analyzes the application of swarm metrics to different swarm visualizations and tasks. A brief overview of the visualizations is provided, along with a description of the heuristic metrics and the analysis. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2701973.2702046 | HRI (Extended Abstracts) |
Keywords | Field | DocType |
design,human factors,visualizations,measurements,complexity measures,measurement,metrics,swarms,performance measures | Heuristic,Swarm behaviour,Heuristic evaluation,Visualization,Computer science,Simulation,Artificial intelligence,Robot | Conference |
Citations | PageRank | References |
3 | 0.40 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthew D. Manning | 1 | 3 | 0.40 |
| Caroline E. Harriott | 2 | 26 | 5.67 |
| Sean Timothy Hayes | 3 | 3 | 0.40 |
| Julie A. Adams | 4 | 392 | 53.75 |
| Adriane E. Seiffert | 5 | 4 | 1.10 |