Abstract — Robots that work alongside us in our homes and workplaces could extend the time an elderly person can live at home, provide physical assistance to a worker on an assembly line, or help with household chores. In order to assist us in these ways, robots will need to successfully perform manipulation tasks within human environments. Human environments present special challenges for robot manipulation since they are complex, dynamic, uncontrolled, and difficult to perceive reliably. In this paper we present a behavior-based control system that enables a humanoid robot, Domo, to help a person place objects on a shelf. Domo is able to physically locate the shelf, socially cue a person to hand it an object, grasp the object that has been handed to it, transfer the object to the hand that is closest to the shelf, and place the object on the shelf. We use this behavior-based control system to illustrate three themes that characterize our approach to manipulation in human environments. The first theme, cooperative manipulation, refers to the advantages that can be gained by having the robot work with a person to cooperatively perform manipulation tasks. The second theme, task relevant features, emphasizes the benefits of carefully selecting the aspects of the world that are to be perceived and acted upon during a manipulation task. The third theme, let the body do the thinking, encompasses several ways in which a robot can use its body to simplify manipulation tasks. 1 Fig. 1. The humanoid robot Domo used in this paper. I.

Experimental results in psychology have shown the important role of manipulation in guiding infant development. This has inspired work in developmental robotics as well. In this case, however, the benefits of this approach has been limited by the intrinsic difficulties of the task. Controlling the interaction between the robot and the environment in a meaningful and safe way is hard especially when little prior knowledge is available. We push the idea that haptic feedback can enhance the way robots interact with unmodeled environments. We approach grasping and manipulation as tasks driven mainly by tactile and force feedback. We implemented a grasping behavior on a robotic platform with sensitive tactile sensors and compliant actuators; the behavior allows the robot to grasp objects placed on a table. Finally, we demonstrate that the haptic feedback originated by the interaction with the objects carries implicit information about their shape and can be useful for learning.

Robots and humans receive partial, fragmentary hints about the world’s state through their respective sensors. In this paper, we focus on some fundamental problems in perception that have attracted the attention of researchers in both robotics and infant development: object segregation, intermodal inte-gration, and the role of embodiment. We concentrate on identifying points of contact between the two fields, and also important questions identified in one field and not yet addressed in the other. For object segregation, both fields have examined the idea of using “key events ” where perception is in some way simplified and the infant or robot acquires knowledge that can be exploited at other times. We examine this parallel research in some detail. We propose that the identification of the key events themselves constitutes a point of contact between the fields. And although the specific algorithms used in robots are not easy to relate to infant development, the overall “algorithmic skeleton ” formed by the set of algorithms needed to identify and exploit key events may in fact form a basis for mutual dialogue.

Robots and humans receive partial, fragmentary hints about the world’s state through their respective sensors. These hints – tiny patches of light intensity, frequency components of sound, etc. – are far removed from the world of objects we feel we perceive so effortlessly around us. The study of infant development and the construction of robots are both deeply concerned with how this apparent gap between the world and our experience of it is bridged. In this paper, we focus on some fundamental problems in perception that have attracted the attention of researchers in both robotics and infant development. Our goal is to identify points of contact already existing between the two fields, and also important questions identified in one field that could fruitfully be addressed in the other. We start with the problem of object segregation: how do infants and robots determine visually where one object ends and another begins? For object segregation, both fields have examined the idea of using “key events ” where perception is in some way simplified and the infant or robot acquires knowledge that can be exploited at other times. We propose that the identification of the key events themselves constitutes a point of contact between the fields. And although the specific algorithms used in robots do not necessarily map directly to infant strategies, the overall “algorithmic skeleton ” formed by the set of algorithms needed to identify and exploit key events may in fact form a basis for mutual dialogue. We then look more broadly at the role of embodiment in humans and robots, and see the opportunities it affords for development.