In this paper, we consider the problem of determining the elasticity properties of deformable objects with a mobile manipulator equipped with a force sensorb. We learn the parameters by establishing a relation between the applied forces and the corresponding surface deformations. To determine the parameters, we minimize the difference between the observed surface of an object that is deformed by a real manipulator and the deformed surface obtained with a deformation simulator based on finite element methods. To establish the correspondences between the surfaces, our approach applies a 3D registration technique based on point-clouds which is used as the basis for comparing the results of the simulation system with the observations of the real deformations. As we demonstrate in real-world experiments, our system is able to estimate appropriate parameters that can be used to predict future deformations. This information can directly be incorporated into motion planning approaches that are designed for robots operating with deformable objects.

In this paper, we consider the problem of mobile robots navigating in environments with non-rigid objects. Whereas robots can plan their paths more effectively when they utilize the information about the deformability of objects, they also need to consider the influence of the interaction with the deformable objects on their measurements during the execution of their navigation task. In this paper, we present a probabilistic approach to identify the measurements influenced by the deformable objects. Based on a learned statistics about the influence of the deformable objects on the measurements, the robot is able to perform a sensor-based collision avoidance of unforeseen objects. We present experiments carried out with a real robot that illustrate the practicability of our approach.

Abstract Collision handling is a comparatively time‐consuming task in dynamic simulations and the computational efficiency of collision handling techniques can vary significantly dependent on the spatial configuration of the environment. These issues have to be addressed in interactive simulations such as games or surgical simulators, where a pre‐defined response time should be guaranteed for each simulation step. We present a time‐critical collision handling approach for deformable objects. The technique employs spatial subdivision for the detection of collisions and penetration depth information is computed to estimate penalty forces. Detection, penetration depth estimation, and response are divided into atomic tasks. In case of an interruption, the algorithm basically resumes in the next time step. If collisions are not completely handled in one simulation step, the algorithm ensures that persistent collisions are handled in a subsequent simulation step. If an exact response cannot be computed in a given time frame, the algorithm efficiently approximates penalty forces for colliding points. Experiments indicate that the proposed technique provides a physically plausible collision handling in the case of incomplete or inconsistent collision information. User‐defined limits for the computation time can be guaranteed with an efficiency gain of up to factor three. Copyright © 2009 John Wiley & Sons, Ltd.