Projekt per år
Sammanfattning
To increase flexibility in the manufacturing industry implies a loss of a fixed structure of the industrial environment, which increases the uncertainties in the shared workspace between humans and robots. Two methods have been proposed in this thesis to mitigate such uncertainty. First, null-space motion was used to increase the accuracy of kinesthetic teaching by reducing the joint static friction, or stiction, without altering the execution of the robotic task. This was possible since robots used in HRC, i.e., collaborative robots, are often designed with additional degrees of freedom (DOFs) for a greater dexterity. Second, to perform effective corrections of the motion of the robot through kinesthetic teaching in partially-unknown industrial environments, a fast identification of the source of robot–environment contact is necessary. Fast contact detection and classification methods in literature were evaluated, extended, and modified to use them in kinesthetic teaching applications for an assembly task. For this, collaborative robots that are made compliant with respect to their external forces/torques (as an active safety mechanism) were used, and only embedded sensors of the robot were considered.
Moreover, safety is a major concern when robotic motion occurs in an inherently uncertain scenario, especially if humans are present. Therefore, an online variation of the compliant behavior of the robot during its manual guidance by a human operator was proposed to avoid undesired parts of the workspace of the robot. The proposed method used safety control barrier functions (SCBFs) that considered the rigid-body dynamics of the robot, and the method’s stability was guaranteed using a passivity-based energy-storage formulation that includes a strict Lyapunov function.
All presented methods were tested experimentally on a real collaborative robot.
Originalspråk | engelska |
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Kvalifikation | Licentiat |
Tilldelande institution |
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Handledare |
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Sponsorer för avhandling | |
Tilldelningsdatum | 2023 jan. 17 |
Utgivningsort | Lund, Sweden |
Utgåva | TRFT-3278 |
Förlag | |
Status | Published - 2023 jan. 17 |
Ämnesklassifikation (UKÄ)
- Robotik och automation
- Reglerteknik
Fingeravtryck
Utforska forskningsämnen för ”Human-Robot Collaboration for Kinesthetic Teaching”. Tillsammans bildar de ett unikt fingeravtryck.-
RobotLab LTH
Bagge Carlson, F. (Forskare), Johansson, R. (Forskare), Karlsson, M. (Forskare), Olofsson, B. (Forskare), Robertsson, A. (Forskare), Robertz, S. (Forskare), Haage, M. (Forskare), Malec, J. (Forskare), Nilsson, K. (Forskare), Nugues, P. (Forskare), Stenmark, M. (Forskare), Topp, E. A. (Forskare), Krueger, V. (Forskare), Åström, H. (Forskare), Mayr, M. (Forskare), Salt Ducaju, J. (Forskare), Nishimura, M. (Administratör), Wisbrant, J. (Projektkommunikatör), Dürr, A. (Forskare), Mayr, M. (Forskare), Nugues, P. (Forskare), Klang, M. (Forskningsingenjör), Klöckner, M. (Forskare), Nardi, L. (Forskare), Ahmad, F. (Forskare), Oxenstierna, J. (Forskare), Rizwan, M. (Forskare), Reichenbach, C. (Forskare), Bergström, J. (Forskare), Dell'Unto, N. (Forskare), Maunsbach, L. (Forskare), Åström, K. (Forskare), Blomdell, A. (Forskningsingenjör), Magnusson, M. (Forskare), Fransson, P.-A. (Forskare), Karayiannidis, Y. (Forskare), Johansson, A. T. (Forskare), Jia, Z. (Forskare), Laban, L. (Forskare), Wingqvist, B. (Forskare), Guberina, M. (Forskare), Jena, A. (Forskare), Westin, E. (Administratör), Frick, C. (Administratör), Pisarevskiy, A. (Forskningsingenjör), Nilsson, A. (Forskningsingenjör), Reitmann, S. (Forskare), Hvarfner, C. (Forskare), Stoltenberg, P. (Forskare) & Fregnan, S. (Forskare)
1993/01/01 → …
Projekt: Forskning
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Human-Robot Collaboration for Kinesthetic Teaching
Salt Ducaju, J. (Forskarstuderande), Johansson, R. (Forskare) & Olofsson, B. (Forskare)
2019/02/01 → 2024/01/31
Projekt: Avhandling