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The gripper finger design is a recurring problem in many robotic grasping platforms used in industry. The task of switching the gripper configuration to accommodate for a new batch of objects typically requires engineering expertise, and is a lengthy and costly iterative trial-and-error process. One of the open challenges is the need for the gripper to compensate for uncertainties inherent to the...
Peg-in-Hole actions play an important role in industrial assembly. In this paper, we present a system which performs such actions after learning by human demonstration. Strategies for getting robust human-demonstrated PiH trajectories are investigated, and a number of PiH experiments are conducted to verify the performance of the proposed approach. The results show that our approach leads to a high...
A large part of industrial assembly tasks can be broken down to permutations of Peg-in-Hole actions. In this paper we compare the success rate of such actions using traditional robot control to an adaptive control strategy based on Dynamic Motor Primitives. Both methods use vision-based pose estimation to locate the peg and the hole in the workspace of an industrial robot, and a dexterous gripper...
The goal of this study is to provide an architecture for a generic definition of robot manipulation actions. We emphasize that the representation of actions presented here is “procedural”. Thus, we will define the structural elements of our action representations as execution protocols. To achieve this, manipulations are defined using three levels. The toplevel defines objects, their relations and...
Autonomous robots are faced with the problem of encoding complex actions (e.g. complete manipulations) in a generic and generalizable way. Recently we had introduced the Semantic Event Chains (SECs) as a new representation which can be directly computed from a stream of 3D images and is based on changes in the relationships between objects involved in a manipulation. Here we show that the SEC framework...
To control the motion of a humanoid robot along a desired trajectory in contact with a rigid object, we need to take into account forces that arise from contact with the surface of the object. In this paper we propose a new method that enables the robot to adapt its motion to different surfaces. The initial trajectories are encoded by dynamic movement primitives, which can be learned from visual feedback...
For effective use of learning by imitation with a robot, it is necessary that the robot can adapt to the current state of the external world. This paper describes an optimization approach that enables the generation of a new motion trajectory, which accomplishes the task in a given situation, based on a library of example movements. New movements are generated by applying statistical methods, where...
In this paper we describe the use of a standard game console joystick, namely the Nintendo WIIMOTE, for an active real-time 3D marker tracking. We show the ease of applicability of inexpensive and robust standard game controllers for 3D object tracking, e.g. to track an infrared source in 3D space. Recovering the 3D information using stereo vision is still one of the major research areas in computer...
There are many situations in which an object that needs to be grasped is not graspable, but could be grasped if it was situated at a different location. By applying nonprehensile manipulation actions such as poking, the object can be moved to a new location without first being grasped. We consider these issues in the context of an artificial cognitive system. The goal of the paper is twofold; firstly,...
In the past, nonlinear dynamic systems have been proposed as a suitable representation for motor control. It has been shown that it is possible to learn desired complex control policies by a nonlinear transformation of an existing simpler control policy, which is based on a canonical dynamic system. The resulting control policies were termed dynamic movement primitives. The main result of this paper...
General-purpose autonomous robots need to have the ability to sequence and adapt the available sensorimotor knowledge, which is often given in the form of movement primitives. In order to solve a given task in situations that were not considered during the initial learning, it is necessary to adapt trajectories contained in the library of primitive motions to new situations. In this paper we explore...
In this paper we study object learning and recognition on a humanoid robot with foveated vision. The developed approach is view-based and can learn viewpoint-independent representations for object recognition. The training data is collected statistically and in an interactive way where a human instructor freely shows the object from a number of different viewpoints. The proposed system was fully implemented...
In this paper we describe and experimentally evaluate how to model, control, and use the capabilities of a humanoid visual system with foveated vision. We present a computational process that can be utilized to identify and update the parameters of the robot's eyes under motion, which enables the use of 3D vision on an active humanoid head. We also derive the formulas expressing the geometry of our...
In this paper we study object recognition on a humanoid robotic head. The head is equipped with a stereo vision system with two cameras in each eye, where the cameras have lenses with different view angles. Such a system models the foveated structure of a human eye. To facilitate the pursuit of moving objects, we provide mathematical analysis that enables the robot to guide the narrow-view cameras...
The recognition and synthesis of parametric movements play an important role in human-robot interaction. To understand the whole purpose of an arm movement of a human agent, both its recognition (e. g., pointing or reaching) as well as its parameterization (i. e., where the agent is pointing at) are important. Only together they convey the whole meaning of an action. Similarly, to imitate a movement,...
The goal of this paper is to investigate how to acquire useful action knowledge by observing the results of exploratory actions on objects. We focus on poking as a representative type of nonprehensile manipulation. Poking can be defined as a short term pushing action. Here we propose an explorative process that allows the robot to learn the relationship between the point of contact on the object boundary...
The design and construction of truly humanoid robots that can perceive and interact with the environment depends significantly on their perception capabilities. In this paper we present the Karlsruhe Humanoid Head, which has been designed to be used both as part of our humanoid robots ARMAR-IIIa and ARMAR-IIIb and as a stand-alone robot head for studying various visual perception tasks in the context...
In this video presentation we introduce a 50 degrees of freedom humanoid robot, CB - ComputationalBrain [1]. CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real world contexts, as humans do. In so doing, we focus on utilising a system that is closer to humans - in sensing, kinematics configuration...
We present a new learning framework for synthesizing goal-directed actions from example movements. The approach is based on the memorization of training data and locally weighted regression to compute suitable movements for a large range of situations. The proposed method avoids making specific assumptions about an adequate representation of the task. Instead, we use a general representation based...
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