Abstract
We propose a new type of artificial potential field, that we call hybrid potential field, to navigate a robot in situations in which the environment is known except for unknown and possibly moving obstacles. We show how to compute hybrid potential fields in real time and use them to control the motions of a real robot. Our method is tested on both a real robot and a simulated one. We present a feature matching approach for position error correction that we have validated experimentally with our mobile robot. We show extensive simulation results with up to 50 randomly moving obstacles.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 149-165 |
| Number of pages | 17 |
| Journal | Autonomous Robots |
| Volume | 1 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 1995 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- artificial potential fields
- collision avoidance
- moving obstacles
- robot navigation
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