Social Robot Navigation

Mobile robots that encounter people on a regular basis must react to them in some way. While traditional robot control algorithms treat all unexpected sensor readings as objects to be avoided, we argue that robots that operate around people should react socially to those people, following the same social conventions that people use around each other. This thesis presents our COMPANION framework: a Constraint-Optimizing Method for Person-Acceptable NavigatION. COMPANION is a generalized framework for representing social conventions as components of a constraint optimization problem, which is used for path planning and navigation. Social conventions, such as personal space and tending to the right, are described as mathematical cost functions that can be used by an optimal path planner. These social conventions are combined with more traditional constraints, such as minimizing distance, in a flexible way, so that additional constraints can be added easily. We present a set of constraints that specify the social task of traveling around people. We explore the implementation of this task first in simulation, where we demonstrate a robot's behavior in a wide variety of scenarios. We also detail how a robot's behavior can be changed by using different relative weights between the constraints or by using constraints representing different sociocultural conventions. We then explore the specific case of passing a person in a hallway, using the robot Grace. Through a user study, we show that people interpret the robot's behavior according to human social norms, and also that people ascribe different personalities to the robot depending on its level of social behavior. In addition, we present an extension of the COMPANION framework that is able to represent joint tasks between the robot and a person. We identify the constraints necessary to represent the task of having a robot escort a person while traveling side-by-side. In simulation, we show the capability of this representation to produce behaviors such as speeding up or slowing down to travel together around corners, as well as complex maneuvers to travel through narrow chokepoints and return to a side-by-side formation. Finally, we present a newly designed robot, Companion, that is intended as a platform for general social human-robot research. Companion is a holonomic robot, able to move sideways without turning first, which we believe is an important social capability. We detail the design and capabilities of this new platform. As a whole, this thesis demonstrates both a need for, and an implementation and evaluation of, robots that navigate around people according to social norms.

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