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This paper describes the design and preliminary implementation of two distributed smart camera applications: a fall detector and an object finder. These functions are part of a novel suite of applications being developed to address “aging in place” health care technologies. Our approach to these applications is unique in that they are based heavily on video(More)
We describe a methodology for creating new technologies for assisted living in residential environments. The number of eldercare clients is expected to grow dramatically over the next decade as the baby boom generation approaches 65 years of age. The UMass/Smith ASSIST framework aims to alleviate the strain on centralized medical providers and community(More)
In large scale surveillance applications, coherent presentation of data coming from myriad sensors becomes a problem. For example, tasks such as "locate an intruder" are no longer easy when the user is facing a room of monitors connected to hundreds of cameras. Therefore, there is a need for a system that allows the user to easily navigate the data space.(More)
This paper advocates an approach for learning communicative actions and manual skills in the same framework. We exploit a fundamental relationship between the structure of motor skills, intention, and communication. Communicative actions are acquired using the same learning framework and the same primitive states and actions that the robot uses to construct(More)
We describe a method for predicting user intentions as part of a human-robot interface. In particular, we show that <i>funnels</i>, i.e., geometric objects that partition an input space, provide a convenient means for discriminating individual objects and for clustering sets of objects for hierarchical tasks. One advantage of the proposed implementation is(More)
Software tools for programming autonomous systems that are embedded in unstructured environments are increasingly important in robotics. We introduce a layered software architecture designed to facilitate the construction of hierarchical models for adaptive control programs that are learned and that can be transferred to related contexts and new robots. We(More)
This paper presents a learning framework that enables a robot to learn comprehensive policies autonomously from a series of incrementally more challenging tasks designed by a human teacher. Psychologists have shown that human infants rapidly acquire general strategies and then extend that behavior with contingencies for new situations. This strategy allows(More)
Smart agents are equipped with sensors that enable them to be sensitive to their surrounding environment. However, the mapping of multiple raw streams of sensory data to the appropriate actions is not an easy problem, especially when multiple conflicting objectives are involved. This type of multi-sensor fusion problem through the domain of power management(More)