The visual active memory perspective on integrated recognition systems

2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)

2012

Abstract-The ability to manipulate deformable objects, such as textiles or paper, is a major prerequisite to bringing the capabilities of articulated robot hands closer to the level of manual intelligence exhibited by humans. We concentrate on the manipulation of paper, which affords us a rich interaction domain that has not yet been solved for anthropomorphic robot hands. Robust tracking and physically plausible modeling of the paper as well as feedback based robot control are crucial components for this task. This paper makes two novel contributions to this area. The first concerns real-time modeling and visual tracking. Our technique not only models the bending of a sheet of paper, but also paper crease lines which allows us to monitor deformations. The second contribution concerns enabling an anthropomorphic robot to fold paper, and is accomplished by introducing a set of tactile-and vision-based closed loop controllers.

Section: Robot Systemmentioning

confidence: 99%

Folding paper with anthropomorphic robot hands using real-time physics-based modeling

Elbrechter

2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)

2012

“…Data flow and inter process communication (IPC) structure of the setup. IPC is implemented using three event driven "Active Memory" [16] nodes. For each camera a dedicated image capturing and 2D marker detection process feeds the "Paper 2D" node.…”

Section: System Overviewmentioning

confidence: 99%

Bi-manual robotic paper manipulation based on real-time marker tracking and physical modelling

Elbrechter

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

2011

Self Cite

The ability to manipulate deformable objects, such as textiles or paper, is a major prerequisite to bringing the capabilities of articulated robot hands closer to the level of manual intelligence exhibited by humans. We concentrate on the manipulation of paper, which affords us a rich interaction domain and that has not yet been solved for anthropomorphic robot hands. A key ability needed for this is the robust tracking and modelling of paper under conditions of occlusion and strong deformation. We present a marker based framework that realizes these properties robustly and in real-time. We compare a purely mathematical representation of the paper manifold with a soft-body-physics model and demonstrate the use of our visual tracking method to facilitate the coordination of two anthropomorphic 20 DOF Shadow Dexterous Hands while they grasp a flat-lying piece of paper, using a combination of visually guided bulging and pinching.

“…This reflects the difficulty to simultaneously serve the demanding goals of task-and config-interaction. A few examples of such systems acting in a robotics or pure vision domain can be found in [2,3,4,5]. Some of our own earlier work along these lines is summarised in [6,7].…”

Section: A Dual Interaction Perspective On Artificial Systemsmentioning

confidence: 99%

A Dual Interaction Perspective for Robot Cognition: Grasping as a “Rosetta Stone”

Perspectives of Neural-Symbolic Integration

Steil

2007

Summary. One of the major milestones to higher cognition may be the ability to shape movements that involve very complex interactions with the environment. Based on this hypothesis we argue that the study and technical replication of manual intelligence may serve as a "Rosetta Stone" for designing cognitive robot architectures. The development of such architectures will strongly benefit if improvements to their interaction capabilities in the task domain become paired with efficient modes of interaction in the domain of configuring and restructuring such systems. We find that this "dual interaction perspective" is closely connected with the challenge of integrating holistic and symbolic aspects of representations. In the case of grasping, this requires a very tight marriage between continuous control and more discrete, symbol-like representations of contact and object states. As a concrete implementation, we propose a two layered architecture, where the lower, subsymbolic layer offers a repository of elementary dynamical processes implemented as specialised controllers for sensori-motor primitives. These controllers are represented and coordinated in the upper, symbolic layer, which employs a hierarchy of state machines. Their states represent semantically related classes of dynamic sensori-motor interaction patterns. We report on the application of the proposed architecture to a robot system comprising a 7-DOF redundant arm and a five-fingered, 20-DOF anthropomorphous manipulator. Applying the dual interaction approach, we have endowed the robot with a variety of grasping behaviours, ranging from simple grasping reflexes over visually instructed "imitation grasping" to grasping actions initiated in response to spoken commands. We conclude with a brief sketch of cognitive abilities that we now feel within close reach for the described architecture.