6 accepted papers
Capturing scene dynamics and predicting the future scene state is challenging but essential for robotic manipulation tasks, especially when the scene contains both rigid and deformable objects. In this work, we contribute a simulation environment and generate a novel dataset for task-specific manipu…
Understanding the effects of actions is essential for planning and executing robot tasks. By imagining possible action consequences, a robot can choose specific action parameters to achieve desired goal states. We present an approach for parametrizing pushing actions based on learning internal predi…
Understanding spatial relations is a key element for natural human-robot interaction. Especially, a robot must be able to manipulate a given scene according to a human verbal command specifying desired spatial relations between objects. To endow robots with this ability, a suitable representation of…
Dynamic systems are a practical alternative to motion planning in executing robot actions. They are of particular interest in Learning from Demonstration, as here we aim to carry out actions in a certain fashion, without a model or in-depth knowledge about the world, which might be difficult to achi…
Reliable execution of robot manipulation actions in cluttered environments requires that the robot is able to understand relations between objects and reason about consequences of actions applied to these objects. We present an approach for extracting physically plausible support relations between o
Robotic coverage path planning describes the problem of determining a configuration space trajectory for successively covering a specified workspace target area with the robot's end-effector. Performing coverage path planning for mobile robots further requires solving the problem of robot placement,…