King's College London
Learning Singularity Avoidance (64.24 MB)

Learning Singularity Avoidance - Data using a real world 7 link sawyer robot and simulated 3 link planar system

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posted on 2021-09-13, 18:33 authored by Jeevan Manavalan
This dataset contains both real world and simulated data. The real world data consists of 50 trajectories of 7DOF Jointspace data recorded kinaesthetically using the Sawyer robot. Each demonstration has 1) a task space component where the sawyer moves from a starting position to anywhere on a drawer and 2) a null space component where the system is closing the drawer. The constraint in the null space limits movement of the system to the x-axis. These can be read as text files. The simulated data consists of 3 sets of 50 trajectories of 3DOF Jointspace data in a planar system. In each set the system is constrained by one of the 3 constraints: 1) X and Y, 2) X and Theta and 3) Y and Theta. These are stored as matlab data. For further details please refer to the paper: Learning Singularity Avoidance Manavalan, J. & Howard, M. J. W., 2019, IEEE/RSJ International Conference on Intelligent Robots and Systems.




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Jeevan Manavalan - King's College London