No abstract

-Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With Rollin' Justin a mobile robotic system and research platform is presented that allows the implementation and demonstration of sophisticated control algorithms and dexterous manipulation. Important problems of service robotics such as mobile manipulation and strategies for using the increased workspace and redundancy in manipulation task can be studied in detail. This paper gives an overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system Justin into Rollin' Justin, a fully self-sustaining mobile research platform.

Abstract-The mobile humanoid Rollin'Justin is a versatile experimental platform for research in manipulation tasks. Previously, different state of the art control methods and first autonomous task execution scenarios have been demonstrated. In this video two new applications with challenging task requirements are presented. One is the catching of one or even two flying balls using all of Justin's degrees of freedom. The other is the autonomous preparation of coffee. Both applications need adequate sensors to support local referencing. The required precision in position and timing is realized in software, using the sensor information, taking the varying precision of Justin's kinematic sub-chains into account and handling all timings in sub-millisecond range.

This paper presents the first two members of the new generation of CLASH hands, which exploit low cost actuation and rapid prototyping to create antagonistic modular and lightweight hands and grippers. The hands approach the robustness of the DLR Awiwi hand with a much lower complexity and cost. To reduce the number of required actuators, a differential coupling mechanism for underactuated fingers was developed, along with a new mechanism that uses variable stiffness actuation in order to increase the workspace of underactuated fingers. The hands provide a research platform for both hand-in-hand and robotic grasping. Design aspects are discussed, and an initial experimental validation verifies the hands' performance.

No abstract

Many houseworks such as cleaning the floor or wiping the windows require to manipulate tools over wide areas. It is necessary to move along a path while manipulating a tool with the whole body and applying exactly the right amount of force to successfully accomplish the task. So mastering such a challenge demands detailed knowledge about the involved objects and the underlying process models. Reasoning about an appropriate parameterization of the task is thereby essential. In this paper we propose a combination of object-centered hybrid reasoning and compliant force control to solve complex wholebody mobile manipulation issues. Depending on the objects involved in the task, an appropriate controller is selected and automatically parameterized. The methods are validated in an elaborate experiment on the humanoid robot Rollin' Justin.

Abstract-Generalising dexterous grasps to novel objects is an open problem. We show how to learn grasps for high DoF hands that generalise to novel objects, given as little as one demonstrated grasp. During grasp learning two types of probability density are learned that model the demonstrated grasp. The first density type (the contact model) models the relationship of an individual finger part to local surface features at its contact point. The second density type (the hand configuration model) models the whole hand configuration during the approach to grasp. When presented with a new object, many candidate grasps are generated, and a kinematically feasible grasp is selected that maximises the product of these densities. We demonstrate 31 successful grasps on novel objects (an 86% success rate), transferred from 16 training grasps. The method enables: transfer of dexterous grasps within object categories; across object categories; to and from objects where there is no complete model of the object available; and using two different dexterous hands.

The spring loaded inverted pendulum (SLIP) model has been extensively shown to be fundamental for legged locomotion. However, the way this low-order template model dynamics is anchored in high-dimensional articulated multibody systems describing compliantly actuated robots (and animals) is not obvious and has not been shown so far. In this paper, an articulated leg mechanism and a corresponding quadrupedal robot design are introduced, for which the natural oscillation dynamics is structurally equivalent to the SLIP. On the basis of this property, computationally simple and robust control methods are proposed, which implement the gaits of pronking, trotting, and dynamic walking in the real robotic system. Experiments with a compliantly actuated quadruped featuring only low performance electrical drives validate the effectiveness of the proposed approach.