Name
Abstract | ||
|---|---|---|
Models of human behaviour, such as pedestrian flows, are beneficial for safe and efficient operation of mobile robots. We present a new methodology for benchmarking of pedestrian flow models based on the afforded safety of robot navigation in human-populated environments. While previous evaluations of pedestrian flow models focused on their predictive capabilities, we assess their ability to support safe path planning and scheduling. Using real-world datasets gathered continuously over several weeks, we benchmark state-of-the-art pedestrian flow models, including both time-averaged and time-sensitive models. In the evaluation, we use the learned models to plan robot trajectories and then observe the number of times when the robot gets too close to humans, using a predefined social distance threshold. The experiments show that while traditional evaluation criteria based on model fidelity differ only marginally, the introduced criteria vary significantly depending on the model used, providing a natural interpretation of the expected safety of the system. For the time-averaged flow models, the number of encounters increases linearly with the percentage operating time of the robot, as might be reasonably expected. By contrast, for the time-sensitive models, the number of encounters grows sublinearly with the percentage operating time, by planning to avoid congested areas and times. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IROS45743.2020.9341672 | IROS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 15 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tomas Vintr | 1 | 7 | 3.63 |
| Zhi Yan | 2 | 6 | 5.93 |
| Kerem Eyisoy | 3 | 0 | 0.34 |
| Filip Kubis | 4 | 0 | 0.34 |
| Jan Blaha | 5 | 0 | 1.01 |
| Jirí Ulrich | 6 | 1 | 1.06 |
| Chittaranjan Srinivas Swaminathan | 7 | 4 | 1.54 |
| Sergi Molina Mellado | 8 | 3 | 2.11 |
| Tomasz Kucner | 9 | 64 | 7.84 |
| Martin Magnusson | 10 | 71 | 10.10 |
| Grzegorz Cielniak | 11 | 316 | 34.34 |
| Jan Faigl | 12 | 336 | 42.34 |
| Tom Duckett | 13 | 14 | 3.27 |
| Achim J. Lilienthal | 14 | 1468 | 113.18 |
| Tomás Krajník | 15 | 422 | 37.83 |