Christoph Borst

A Humanoid Two-Arm System for Dexterous Manipulation

This paper presents a humanoid two-arm system developed as a research platform for studying dexterous two-handed manipulation. The system is based on the modular DLR-Lightweight-Robot-III and the DLR-Hand-II. Two arms and hands are combined with a three degrees-of-freedom movable torso and a visual system to form a complete humanoid upper body. In this paper we present the design considerations and give an overview of the different sub-systems. Then, we describe the requirements on the software architecture. Moreover, the applied control methods for two-armed manipulation and the vision algorithms used for scene analysis are discussed

A fast and robust grasp planner for arbitrary 3D objects

In order to grasp and manipulate real world objects, grasp planning systems are required, and they have to be very fast in order to be integrated in online planning systems for robots. This paper presents a method to compute a desirable grasp quality measure very fast and accurately. Based on this measure a heuristic approach towards fast planning of precision grasps for arbitrarily shaped 3D objects is described. A number of feasible grasp candidates are generated heuristically. These grasp candidates are qualified using the described grasp quality measure and the best candidate is chosen. The planned grasps are robust with respect to grasp placement. It is shown that only a relatively small number of grasp candidates has to be generated in order to obtain a good, although not optimal, grasp.

Capturing robot workspace structure: representing robot capabilities

Humans have at some point learned an abstraction of the capabilities of their arms. By just looking at the scene they can decide which places or objects they can easily reach and which are difficult to approach. Possessing a similar abstraction of a robot arms capabilities in its workspace is important for grasp planners, path planners and task planners. In this paper, we show that robot arm capabilities manifest themselves as directional structures specific to workspace regions. We introduce a representation scheme that enables to visualize and inspect the directional structures. The directional structures are then captured in the form of a map, which we name the capability map. Using this capability map, a manipulator is able to deduce places that are easy to reach. Furthermore, a manipulator can either transport an object to a place where versatile manipulation is possible or a mobile manipulator or humanoid torso can position itself to enable optimal manipulation of an object.

Grasp planning: how to choose a suitable task wrench space

For the evaluation of grasp quality, different measures have been proposed that are based on wrench spaces. Almost all of them have drawbacks that derive from the non-uniformity of the wrench space, composed of force and torque dimensions. Moreover, many of these approaches are computationally expensive. We address the problem of choosing a proper task wrench space to overcome the problems of the non-uniform wrench space and show how to integrate it in a well-known, high precision and extremely fast computable grasp quality measure.

Grasping the dice by dicing the grasp

Many methods for generating and analyzing grasps have been developed in the recent years. They gave insight and comprehension of grasping with robot hands but many of them are rather complicated to implement and of high computational complexity. In this paper we study if the basic quality criterion for grasps, the force-closure property, is in principle easy or difficult to reach. We show that it is not necessary to generate optimal grasps, due to a certain quality measure, for real robot grasping tasks where an average quality grasp is acceptable. We present statistical data that confirm our opinion that a randomized grasp generation algorithm is fast and suitable for the planning of robot grasping tasks.

Calculating hand configurations for precision and pinch grasps

Usually, grasp planning can be split into two phases. In the first phase one tries to find a set of contacts that allow for stable grasping of an object. In the second phase a feasible hand pose that realizes the grasp with a given hand is calculated. While this point is important for a practical grasp planning system, it has either been considered trivial or been solved by crude heuristics in most cases. Here we present an approach for calculating the hand and finger pose for a given grasp. The problem is formulated as a constraint satisfaction problem and then solved using optimization techniques. The method is applied to two different grasp types: the well known precision grasp and the pinch grasp which is preferred by men when grasping small objects.

DLR hand II: experiments and experience with an anthropomorphic hand

At our institute, two generations of antropomorphic hands have been designed. In quite a few experiments and demonstrations we could show the abilities of our hands and gain a lot of experience in what artificial hands can do, what abilities they need and where their limitations lie. In this paper, we would like to give an overview over the experiments performed with the DLR hands, our hands abilities and the things that need to be done in the near future.

A humanoid upper body system for two-handed manipulation

This video presents a humanoid two-arm system developed as a research platform for studying dexterous two-handed manipulation. The system is based on the modular DLR-Lightweight-Robot-III and the DLR-Hand-II. Two arms and hands are combined with a three degrees-of-freedom movable torso and a visual system to form a complete humanoid upper body. The diversity of the system is demonstrated by showing the mechanical design, several control concepts, the application of rapid prototyping and hardware-in-the-loop (HIL) development as well as two-handed manipulation experiments and the integration of path planning capabilities.

Experimental study on impedance control for the five-finger dexterous robot hand DLR-HIT II

This paper presents experimental results on the five-finger dexterous robot hand DLR-HIT II, with Cartesian impedance control based on joint torque and nonlinearity compensation for elastic dexterous robot joints. To improve the performence of the impedance controller, system parameter estimations with extended kalman filter and gravity compensation have been investigated on the robot hand. Experimental results show that, for the harmonic drive robot hand with joint toruqe feedback, accurate position tracking and stable torque/force response can be achieved with cartesian and joint impedance controller. In addition, a FPGA-based control architecture with flexible communication is proposed to perform the designed impedance controller.

The DLR-Crawler: A testbed for actively compliant hexapod walking based on the fingers of DLR-Hand II

Walking is a fascinating way of locomotion that is very robust, especially in unstructured terrain. Many researchers devote their time to understanding its underlying principles and to build robots based on their findings. Using the fingers of DLR-Hand II a six-legged actively compliant walking robot is developed. It is intended to be used as testbed for the evaluation of different force- and position-based leg and gait control algorithms for hexapod walking in rough terrain. Following a brief overview of the finger hardware, the use of fingers as legs is analyzed and discussed. The body geometry as well as the systems constituting the robot are described. The compliance control algorithm used is explained and finally some experimental results are presented.