center for robotics and embedded systems University of Southern California Viterbi School of Engineering


The present state of designing behaviors for humanoid robots can be viewed as analogous to programming a computer using machine language. Even when such complex issues as interaction control and locomotion can be bypassed, programming generally is still pursued in a highly robot-dependent manner. Though roboticists currently use sophisticated tools like human motion capture systems to assist with behavior design, a core tenet of software development-- component reuse-- is frequently overlooked. As a result, a behavior that allows a robot to perform a task will often fail on a different robot, even if the kinematic and dynamic properties between the two robots are highly similar. This problem prevents software reuse and, by extension, limits development of high-level humanoid behaviors for performing a broad range of tasks. This dissertation aims to address the above limitations in the state-of-the-art by first separating humanoid tasks into robot-dependent and robot-independent components, thereby facilitating component reuse, and then identifying and implementing a set of primitive task programs for a humanoid robot that, when executed sequentially and concurrently, allow a broad range of humanoid tasks to be performed. This dissertation presents a framework for integrating a library of performable task behaviors that are portable across many humanoid robots with little or no modification. The framework, called the Task Matrix, provides an application-programming interface (API) to program humanoid robots in an abstract manner; the robot-specific components lie in the implementation of the API. The Task Matrix describes formally how tasks can interact, both in sequence and concurrence. This specification permits complex behaviors to be constructed from a small vocabulary of primitive task behaviors. Such a vocabulary is provided and is applied toward implementing a set of behaviors for executing human occupational tasks. This work is validated on three simulated humanoid robots by performing both the primitive behaviors in various circumstances and complex behaviors composed of the primitives.


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