Projekt per år
Sammanfattning
We propose a generalisation of a behaviour tree and motiongenerator based robot arm policy representation for learning and solving tasks such as contact-rich tasks like peg insertion or pushing an object. We use planning to generate skill sequences needed to execute these tasks and rely on reinforcement learning to obtain parameters of the policy. We assume gaussian processes as a suitable method for this generalisation and present preliminary, promising results from initial experiments.
| Originalspråk | engelska |
|---|---|
| Antal sidor | 2 |
| Status | Published - 2022 |
Ämnesklassifikation (UKÄ)
- Robotteknik och automation
Fingeravtryck
Utforska forskningsämnen för ”Generalizing Behavior Trees and Motion-Generator (BTMG) Policy Representation for Robotic Tasks Over Scenario Parameters”. Tillsammans bildar de ett unikt fingeravtryck.Projekt
- 2 Aktiva
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Efficient Learning of Robot Skills
Mayr, M., Malec, J. & Krueger, V.
2018/09/03 → 2023/09/01
Projekt: Avhandling
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Robotlab LTH
Bagge Carlson, F., Dressler, I., Johansson, R., Ghazaei Ardakani, M., Karlsson, M., Linderoth, M., Olofsson, B., Olsson, T., Robertsson, A., Sörnmo, O., Stolt, A., Robertz, S., Haage, M., Malec, J., Nilsson, K., Nugues, P., Stenmark, M., Topp, E. A., Krueger, V., Åström, H., Greiff, M., Klöckner, M., Mayr, M., Sun, Z., Salt Ducaju, J., Nishimura, M., Wisbrant, J., Andersson, L., Dürr, A., Mayr, M., Åström, H., Nugues, P., Klang, M., Klöckner, M., Lager, M., Nardi, L., Ahmad, F., Oxenstierna, J., Rizwan, M., Reichenbach, C., Bergström, J., Dell'Unto, N., Maunsbach, L., Åström, K., Sminchisescu, C., Flood, G., Blomdell, A., Soltesz, K., Magnusson, M., Fransson, P., Karayiannidis, Y., Johansson, A. T., Jia, Z., Laban, L., Wingqvist, B. & Guberina, M.
1993/01/01 → 2029/12/31
Projekt: Forskning