Alexander Bierbaum

ARMAR-III: An Integrated Humanoid Platform for Sensory-Motor Control

In this paper, we present a new humanoid robot currently being developed for applications in human-centered environments. In order for humanoid robots to enter human-centered environments, it is indispensable to equip them with manipulative, perceptive and communicative skills necessary for real-time interaction with the environment and humans. The goal of our work is to provide reliable and highly integrated humanoid platforms which on the one hand allow the implementation and tests of various research activities and on the other hand the realization of service tasks in a household scenario. We introduce the different subsystems of the robot. We present the kinematics, sensors, and the hardware and software architecture. We propose a hierarchically organized architecture and introduce the mapping of the functional features in this architecture into hardware and software modules. We also describe different skills related to real-time object localization and motor control, which have been realized and integrated into the entire control architecture

Toward humanoid manipulation in human-centred environments

In order for humanoid robots to enter human-centred environments, it is indispensable to equip them with manipulative, perceptive and communicative skills necessary for real-time interaction with the environment and humans. The goal of our work is to provide reliable and highly integrated humanoid platforms which on the one hand allow the implementation and tests of various research activities and on the other hand the realization of service tasks in a household scenario. In this paper, we present a new humanoid robot currently being developed for applications in human-centred environments. In addition, we present an integrated grasping and manipulation system consisting of a motion planner for the generation of collision-free paths and a vision system for the recognition and localization of a subset of household objects as well as a grasp analysis component which provides the most feasible grasp configurations for each object.

A new anthropomorphic robotic hand

This paper presents the new robotic FRH-4 hand. The FRH-4 hand constitutes a new hybrid concept of an anthropomorphic five fingered hand and a three jaw robotic gripper. The hand has a humanoid appearance while maintaining the precision of a robotic gripper. Since it is actuated with flexible fluidic actuators, it exhibits an excellent power to weight ratio. These elastic actuators also ensure that the hand is safe for interacting with humans. In order to fully control the joints, it is equipped with position sensors on all of the 11 joints. The hand is also fitted with tactile sensors based on cursor navigation sensor elements, which allows it to have grasping feedback and the ability for exploration.

Grasp affordances from multi-fingered tactile exploration using dynamic potential fields

In this paper, we address the problem of tactile exploration and subsequent extraction of grasp hypotheses for unknown objects with a multi-fingered anthropomorphic robot hand. We present extensions on our tactile exploration strategy for unknown objects based on a dynamic potential field approach resulting in selective exploration in regions of interest. In the subsequent feature extraction, faces found in the object model are considered to generate grasp affordances. Candidate grasps are validated in a four stage filtering pipeline to eliminate impossible grasps. To evaluate our approach, experiments were carried out in a detailed physics simulation using models of the five-finger hand and the test objects.

A potential field approach to dexterous tactile exploration of unknown objects

Haptic exploration of unknown objects is of great importance for acquiring multi-modal object representations, which enable a humanoid robot to autonomously execute grasping and manipulation tasks. In this paper we present a tactile exploration strategy to guide an anthropomorphic five-finger hand along the surface of previously unknown objects and build a 3D object representation based on acquired tactile point clouds. The proposed strategy makes use of the dynamic potential field approach suggested in the context of mobile robot navigation. To demonstrate the capabilities of this strategy, we conduct experiments in a detailed physics simulation using a model of the five-finger hand. Exploration results of several test objects are given.

Robust shape recovery for sparse contact location and normal data from haptic exploration

3D shape reconstruction of objects from tactile exploration data acquired by a multi-fingered robot hand is an important skill for a humanoid robot system. Tactile exploration data captured using current robot technology is naturally sparse and noisy, therefore a satisfying shape estimate is difficult to achieve. In this paper we describe a robust approach for 3D shape recovery using superquadric functions, which makes use of both contact location and normal information. We present two quality measures and compare to other relevant estimation techniques using representative synthetic contact data.

Force position control for a pneumatic anthropomorphic hand

Robot hands based on fluidic actuators are a promising technology for humanoid robots due to their compact size and excellent power-weight-ratio. Yet, such actuators are difficult to control due to the inherent nonlinearities of pneumatic systems. In this paper we present a control approach based on a simplified model of the fluidic actuator providing force and position control and further fingertip contact detection. We have implemented the method on the microcontroller of the human hand sized FRH-4 robot hand with 8 DoF and present results of several experiments, including system response and force controlled operation.

The OpenGRASP benchmarking suite: An environment for the comparative analysis of grasping and dexterous manipulation

In this work, we present a new software environment for the comparative evaluation of algorithms for grasping and dexterous manipulation. The key aspect in its development is to provide a tool that allows the reproduction of well-defined experiments in real-life scenarios in every laboratory and, hence, benchmarks that pave the way for objective comparison and competition in the field of grasping. In order to achieve this, experiments are performed on a sound open-source software platform with an extendable structure in order to be able to include a wider range of benchmarks defined by robotics researchers. The environment is integrated into the OpenGRASP toolkit that is built upon the OpenRAVE project and includes grasp-specific extensions and a tool for the creation/integration of new robot models. Currently, benchmarks for grasp and motion planningare included as case studies, as well as a library of domestic everyday objects models, and a real-life scenario that features a humanoid robot acting in a kitchen.

Haptic exploration for 3D shape reconstruction using five-finger hands

In order for humanoid robots to enter human-centered environments, it is indispensable to equip them with the ability to recognize and classify objects in such an environment. A promising way to acquire the object models necessary for object manipulation appears in the supplement of the information gathered by computer vision techniques with data from haptic exploration. In this paper we present a framework for haptic exploration which is intended for use with both, a five-finger humanoid robot hand as well as with a human hand. We describe experiments and results on haptic exploration and shape estimation of 2D and 3D objects by the human hand. Volumetric shape data is acquired by a human operator hand using a data glove. The exploring human hand is located by a stereo camera system, whereas the finger configuration is calculated from the glove data.

Tactile object exploration using cursor navigation sensors

In robotic applications tactile sensor systems serve the purpose of localizing a contact point and measuring contact forces. We have investigated the applicability of a sensorial device commonly used in cursor navigation technology for tactile sensing in robotics. We show the potential of this sensor for active haptic exploration. More specifically, we present experiments and results which demonstrate the extraction of relevant object properties such as local shape, weight and elasticity using this technology. Besides its low price due to mass production and its modularity, an interesting aspect of this sensor is that beside a localization of contact points and measurement of the contact normal force also shear forces can be measured. This is relevant for many applications such as surface normal estimation and weight measurements. Scalable tactile sensor arrays have been developed with this sensor which can be arranged as tiles on a surface, e.g. a manipulator.