... | ... | @@ -226,11 +226,11 @@ The following cost functions are currently supported: |
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| `TtcaDca` | The cost function used in the vision-based steering algorithm by Dutra et al. (2016), simplified to our domain. | Dutra | 1,2 |
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| `VanToll` | A custom collision-avoidance cost function that is sometimes used by our own team. | VanToll | - |
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**Notes:**
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(1) This cost function is meant to be used in a gradient-based policy. You are free to use it in a sampling-based policy as well, but it may not behave exactly as intended.
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(2) This cost function does not yet support obstacles. Agents that use this cost function will not avoid obstacles.
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(3) This cost function is under construction, and it does not yet act as intended.
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(4) This cost function also supports global optimization, using a direct port of the ORCA source code.
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(5) This cost function does not yet support global optimization, even though it is theoretically possible.
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*Notes:*
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1. This cost function is meant to be used in a gradient-based policy. You are free to use it in a sampling-based policy as well, but it may not behave exactly as intended.
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2. This cost function does not yet support obstacles. Agents that use this cost function will not avoid obstacles.
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3. This cost function is under construction, and it does not yet act as intended.
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4. This cost function also supports global optimization, using a direct port of the ORCA source code.
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5. This cost function does not yet support global optimization, even though it is theoretically possible.
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Each specific cost function can have its own **specific attributes**. We are currently not listing these attributes here. Instead, they are specified in the (Doxygen) comments of each cost function's C++ header file. For example, the documentation in `core/CostFunctions/RVO.h` describes the parameters of the RVO cost function. Therefore, the best option is to look in the Doxygen comments of the cost function that you want to use. |
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