Toward the control of attention in a dynamically dexterous robot

In the recent successful effort to achieve the spatial two-juggle - batting two freely falling balls into independent stable periodic vertical orbits by repeated impacts with a three degree of freedom robot arm, the authors have found it necessary to introduce a dynamical window manager into their real-time stereo vision. This paper describes these necessary enhancements to the original vision system and then proposes a more formal account of how such a feedback based sensor might be understood to work. Further experimentation will be required to determine the extent to which the analytical model explains (and might thus be used as a tool to improve) the performance of the system presently working in the laboratory

Sequential Composition of Dynamically Dexterous Robot Behaviors

We report on our efforts to develop a sequential robot controller-composition technique in the context of dexterous “batting” maneuvers. A robot with a flat paddle is required to strike repeatedly at a thrown ball until the ball is brought to rest on the paddle at a specified location. The robot’s reachable workspace is blocked by an obstacle that disconnects the free space formed when the ball and paddle remain in contact, forcing the machine to “let go” for a time to bring the ball to the desired state. The controller compositions we create guarantee that a ball introduced in the “safe workspace” remains there and is ultimately brought to the goal. We report on experimental results from an implementation of these formal composition methods, and present descriptive statistics characterizing the experiments.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67990/2/10.1177_02783649922066385.pd

Integrated Circuitry to Detect Slippage Inspired by Human Skin and Artificial Retinas

This paper presents a bioinspired integrated tactile coprocessor that is able to generate a warning in the case of slippage via the data provided by a tactile sensor. Some implementations use different layers of piezoresistive and piezoelectric materials to build upon the raw sensor and obtain the static (pressure) as well as the dynamic (slippage) information. In this paper, a simple raw sensor is used, and a circuitry is implemented, which is able to extract the dynamic information from a single piezoresistive layer. The circuitry was inspired by structures found in human skin and retina, as they are biological systems made up of a dense network of receptors. It is largely based on an artificial retina , which is able to detect motion by using relatively simple spatial temporal dynamics. The circuitry was adapted to respond in the bandwidth of microvibrations produced by early slippage, resembling human skin. Experimental measurements from a chip implemented in a 0.35-mum four-metal two-poly standard CMOS process are presented to show both the performance of the building blocks included in each processing node and the operation of the whole system as a detector of early slippage.Ministerio de Economía y Competitividad TEC2006-12376-C02-01Gobierno de España TEC2006- 1572

Further progress in robot juggling: the spatial two-juggle

We report on our recently achieved spatial two-juggle: the ability to bat two freely falling balls into stable periodic vertical trajectories with a single three degree of freedom robot arm using a real-time stereo camera system for sensory input. After a brief review of the previously reported one-juggle, we describe our initial approach to the two-juggle planning and control problem. We have developed a number of important refinements to our initial strategy in the course of getting the system to work, and these are reported in some detail. The paper concludes with a discussion of some data from typical two-juggle runs in the laboratory

An Active Visual Estimator for Dexterous Manipulation

We present a working implementation of a dynamics based architecture for visual sensing. This architecture provides field rate estimates of the positions and velocities of two independent falling balls in the face of repeated visual occlusions and departures from the field of view. The practical success of this system can be attributed to the interconnection of two strongly nonlinear dynamical systems: a novel triangulating state estimator; and an image plane window controller. We detail the architecture of this active sensor, provide data documenting its performance, and offer an analysis of its soundness in the form of a convergence proof for the estimator and a boundedness proof for the manager

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics

A hierarchical sensorimotor control framework for human-in-the-loop robotic hands.

Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands

Active haptic perception in robots: a review

In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed. In all these contexts, robots are requested to perform tasks within open-ended conditions, possibly dynamically varying. These new requirements ask also for a change of paradigm in the design of robots: on-line and safe feedback motion control becomes the core of modern robot systems. Future robots will learn autonomously, interact safely and possess qualities like self-maintenance. Attaining these features would have been relatively easy if a complete model of the environment was available, and if the robot actuators could execute motion commands perfectly relative to this model. Unfortunately, a complete world model is not available and robots have to plan and execute the tasks in the presence of environmental uncertainties which makes sensing an important component of new generation robots. For this reason, today\u2019s new generation robots are equipped with more and more sensing components, and consequently they are ready to actively deal with the high complexity of the real world. Complex sensorimotor tasks such as exploration require coordination between the motor system and the sensory feedback. For robot control purposes, sensory feedback should be adequately organized in terms of relevant features and the associated data representation. In this paper, we propose an overall functional picture linking sensing to action in closed-loop sensorimotor control of robots for touch (hands, fingers). Basic qualities of haptic perception in humans inspire the models and categories comprising the proposed classification. The objective is to provide a reasoned, principled perspective on the connections between different taxonomies used in the Robotics and human haptic literature. The specific case of active exploration is chosen to ground interesting use cases. Two reasons motivate this choice. First, in the literature on haptics, exploration has been treated only to a limited extent compared to grasping and manipulation. Second, exploration involves specific robot behaviors that exploit distributed and heterogeneous sensory data