Behavior-Based Mobile Manipulation for Drum Sampling

Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA
05/1996; DOI: 10.1109/ROBOT.1996.506521
Source: OAI

ABSTRACT This paper describes an implementation of a behavior-based mobile manipulator capable of autonomously transferring a sample from one drum to a second in unstructured environments. A major contribution of the project was the coherent integration of the arm and base as a cohesive unit, and not just a mobile base with an arm attached. The support for smooth simultaneous operation of all joints on the vehicle facilitated biologically plausible motions, such as arm preshaping. The behavior-based controller used a pseudo-force model, where behaviors add forces and torques to joints and limbs resulting in coordinated motion. The vehicle Jacobian is used to convert the pseudo-forces into joint torques and a pseudo-damping model converts the joint torques into joint velocities. This process allows rapid control of the manipulator without the use of inverse kinematics. A drum sampling task is presented where the vehicle demonstrates how a sample of material could be moved from one drum to another, illustrating the efficacy of the solution.

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    ABSTRACT: This work focuses on robot behaviors which use minimal communication and rely mostly on changes in the environment as their cue for action. The behavior-based paradigm for building autonomous robots has become very popular because of its successes, use of the world as an external memory and replacement of classical planning by agent-environment dynamics. However there are no criteria for evaluating and improving behavior sets. Our aim here is to bridge this gap. We define several criteria (power, usefulness, flexibility, modularity, and, reliability) and investigate the properties of behavior sets using them. We use these criteria to present results on modifications to individual behaviors and addition of new behaviors to the behavior sets. We show how computations related to these criteria can be carried out. We report on guidelines to improve a behavior set.
    Artificial Intelligence 01/2003; · 2.19 Impact Factor
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    ABSTRACT: SYNOPSIS This paper describes the application of behaviour-based control for a mobile manipulation task. It presents a preliminary result in the research into a 'task-robust' controller for a service robot, needed when a robot is used in a human-centred environment. The chosen benchmark task is the co-operative carrying of a long object by a mobile manipulator and a human. The human will guide the task, the mobile manipulator follows, while avoiding obstacles in its path. This paper gives a global overview of the implemented control structure, the resulting behaviour of the mobile manipulator and some goals for the future are presented.

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May 16, 2014