Sample based-optimisation-based planner with signed distance fields cost map
Rapidly-exploring random trees (RRT) and their variant are a very power solution for solving motion planning problem in robotics, but they suffer from finding an optimise solution and the generated path is usually jerky with redundant movements. Sample based-optimisation-based planners benefit the robustness of RRT and the possibility of imposing a cost function. Here in this work, I …
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Dual arm manipulator operating a handwheel
Operating a handwheel with two schunk LWA 4D manipulators. Corresponding paper in IROS 2015.
Motion planning under Cartesian constraints
In this task, an orientation constraint has been imposed to the planner such that the orientation of end effector is fixed during the task. The planner checks the self-collision and collision between robot and the environment. Corresponding paper in IROS 2015.
It often happens that you are interested to know in which area you robot has high manipulability and in which area it has low manipulability. There are several approaches for that. In this work, I implemented the Yoshikawa manipulability index. I discretized the joint space for each joint, then I compute the manipulability index and dump all …
Learning From Demonstration
In this work at first, I recognize the object in the scene and estimate the 6 DOF pose of that. Then I track the object by using particle filter. RGB data acquired from Kinect 2 and turned into PCL pointcloud. I demonstrate a task several times to the robot. In this case, I move an object (a detergent) over …