Averting Robot Eyes

Home robots will cause privacy harms. At the same time, they can provide beneficial services—as long as consumers trust them. This Essay evaluates potential technological solutions that could help home robots keep their promises, avert their eyes, and otherwise mitigate privacy harms. Our goals are to inform regulators of robot-related privacy harms and the available technological tools for mitigating them, and to spur technologists to employ existing tools and develop new ones by articulating principles for avoiding privacy harms. We posit that home robots will raise privacy problems of three basic types: (1) data privacy problems; (2) boundary management problems; and (3) social/relational problems. Technological design can ward off, if not fully prevent, a number of these harms. We propose five principles for home robots and privacy design: data minimization, purpose specifications, use limitations, honest anthropomorphism, and dynamic feedback and participation. We review current research into privacy-sensitive robotics, evaluating what technological solutions are feasible and where the harder problems lie. We close by contemplating legal frameworks that might encourage the implementation of such design, while also recognizing the potential costs of regulation at these early stages of the technology

A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation

Partially-Observable Markov Decision Processes (POMDPs) are typically solved by finding an approximate global solution to a corresponding belief-MDP. In this paper, we offer a new planning algorithm for POMDPs with continuous state, action and observation spaces. Since such domains have an inherent notion of locality, we can find an approximate solution using local optimization methods. We parameterize the belief distribution as a Gaussian mixture, and use the Extended Kalman Filter (EKF) to approximate the belief update. Since the EKF is a first-order filter, we can marginalize over the observations analytically. By using feedback control and state estimation during policy execution, we recover a behavior that is effectively conditioned on incoming observations despite the unconditioned planning. Local optimization provides no guarantees of global optimality, but it allows us to tackle domains that are at least an order of magnitude larger than the current state-of-the-art. We demonstrate the scalability of our algorithm by considering a simulated hand-eye coordination domain with 16 continuous state dimensions and 6 continuous action dimensions

Manifold Representations for Continuous-State Reinforcement Learning

Reinforcement learning (RL) has shown itself to be an effective paradigm for solving optimal control problems with a finite number of states. Generalizing RL techniques to problems with a continuous state space has proven a difficult task. We present an approach to modeling the RL value function using a manifold representation. By explicitly modeling the topology of the value function domain, traditional problems with discontinuities and resolution can be addressed without resorting to complex function approximators. We describe how manifold techniques can be applied to value-function approximation, and present methods for constructing manifold representations in both batch and online settings. We present empirical results demonstrating the effectiveness of our approach

Control of a Robotic Arm Using Low-Dimensional EMG and ECoG Biofeedback

In this dissertation we describe a system that uses a low dimensional input derived from electromyography and electrocorticography data to control a robot. The work involves creating a system that allows signals recorded directly from a human body to allow control of a small robot arm. We compare direct joystick control with electromyogram (EMG) input to determine if one input system is superior, or if the quality of control between them is comparable. We also verify the system that is used to record the electromyogram signals is adaptable to other forms of biosignal input; in particular, direct connection to a human brain via electrocorticography (ECoG). Because of the current limitations in sensing and interpreting biological signals, the dimensionality of the data available through these signals is low. Our system is designed to use these low dimensional data and map specific patterns to resulting actions of a robot arm

An Inexpensive Robot Platform for Teleoperation and Experimentation

Most commercially-available robots are either aimed at the research community, or are designed with a single purpose in mind. The extensive hobbyist community has tended to focus on the hardware and the low-level software aspects. We claim that there is a need for a low-cost, general-purpose robot, accessible to the hobbyist community, with sufficient computation and sensing to run ``research-grade\u27\u27 software. In this paper, we describe the design and implementation of such a robot. We explicitly outline our design goals, and show how a capable robot can be assembled from off-the-shelf parts, for a modest cost, by a single person with only a few tools. We also show how the robot can be used as a low-cost telepresence platform, giving the system a concrete purpose beyond being a low-cost development platform

What do Collaborations with the Arts Have to Say About Human-Robot Interaction?

This is a collection of papers presented at the workshop What Do Collaborations with the Arts Have to Say About HRI , held at the 2010 Human-Robot Interaction Conference, in Osaka, Japan

Picture Composition for a Robot Photographer

We explain how to use simple composition rules to drive an automated, mobile photography system. The composition rules are used to determine both the location for a good photograph, and how to frame that photograph. We describe the composition component in the context of a larger application, a robotic photographer. The robot moves around an area with people in it, opportunistically looking for faces and taking photographs. We describe both how to find faces in the world and how to create “good” photographs of those faces