William D. Smart

Robots for humanity: using assistive robotics to empower people with disabilities

Assistive mobile manipulators (AMMs) have the potential to one day serve as surrogates and helpers for people with disabilities, giving them the freedom to perform tasks such as scratching an itch, picking up a cup, or socializing with their families.

Layered costmaps for context-sensitive navigation.

Many navigation systems, including the ubiquitous ROS navigation stack, perform path-planning on a single costmap, in which the majority of information is stored in a single grid. This approach is quite successful at generating collision-free paths of minimal length, but it can struggle in dynamic, people-filled environments when the values in the costmap expand beyond occupied or free space. We have created and implemented a new method called layered costmaps, which work by separating the processing of costmap data into semantically-separated layers. Each layer tracks one type of obstacle or constraint, and then modifies a master costmap which is used for the path planning. We show how the algorithm can be integrated with the open-source ROS navigation stack, and how our approach is easier to fine-tune to specific environmental contexts than the existing monolithic one. Our design also results in faster path planning in practical use, and exhibits a cleaner separation of concerns that the original architecture. The new algorithm also makes it possible to represent complex cost values in order to create navigation behavior for a wide range of contexts.

Towards more efficient navigation for robots and humans

Effective robot navigation in the presence of humans is hard. Not only do human obstacles move, they react to the movements of the robot according to instinct and social rules. In order to efficiently navigate around each other, both the robot and the human must move in a way that takes the other into account. Failure to do so can lead to a lowering of the perceived quality of the interaction and, more importantly, it can also delay one or both parties, causing them to be less efficient in whatever task they are trying to achieve. In this paper, we present a system capable of creating more efficient corridor navigation behaviors by manipulating existing navigation algorithms and introducing social cues from the robot to the human. We give the results of a user study, demonstrating the effectiveness of our system, and discuss how it can be applied more generally to a wide variety of situations.

Tuning Cost Functions for Social Navigation

Human-Robot Interaction literature frequently uses Gaussian distributions within navigation costmaps to model proxemic constraints around humans. While it has proven to be effective in several cases, this approach is often hard to tune to get the desired behavior, often because of unforeseen interactions between different elements in the costmap. There is, as far as we are aware, no general strategy in the literature for how to predictably use this approach. n nIn this paper, we describe how the parameters for the soft constraints can affect the robots planned paths, and what constraints on the parameters can be introduced in order to achieve certain behaviors. In particular, we show the complex interactions between the Gaussians parameters and elements of the path planning algorithms, and how undesirable behavior can result from configurations exceeding certain ratios. There properties are explored using mathematical models of the paths and two sets of tests: the first using simulated costmaps, and the second using live data in conjunction with the ROS Navigation algorithms.

Seeing is Comforting: Effects of Teleoperator Visibility in Robot-Mediated Health Care

Teleoperated robots can be used to provide medical care to patients in infectious disease outbreaks, alleviating workers from being in dangerous infectious zones longer than absolutely needed. Nevertheless, patients reactions to this technology have not been tested. We test three hypotheses related to patients comfort and trust of the operator and robot in a simulated Ebola Treatment Unit. Our findings suggest patients trust the robot teleoperator more when they can see the teleoperator.

Context-sensitive in-the-world interfaces for mobile manipulation robots

We present an interface that allows users to direct a mobile manipulation robot in tabletop pick-and-place tasks using only their head motions and a single button. The system uses an estimate of the users head pose and a 3d world model maintained by the robot to determine where the user is pointing their head. We give the results of some preliminary evaluations of our system, which suggest that it is both intuitive and effective. We also describe an example trash-sorting application where the user directs a PR2 robot sort objects in to “trash” and “recycle” piles.

Video Manipulation Techniques for the Protection of Privacy in Remote Presence Systems

Systems that give control of a mobile robot to a remote user raise privacy concerns about what the remote user can see and do through the robot. We aim to preserve some of that privacy by manipulating the video data that the remote user sees. Through two user studies, we explore the effectiveness of different video manipulation techniques at providing different types of privacy. We simultaneously examine task performance in the presence of privacy protection. In the first study, participants were asked to watch a video captured by a robot exploring an office environment and to complete a series of observational tasks under differing video manipulation conditions. Our results show that using manipulations of the video stream can lead to fewer privacy violations for different privacy types. Through a second user study, it was demonstrated that these privacy-protecting techniques were effective without diminishing the task performance of the remote user.

Evaluation of physical marker interfaces for protecting visual privacy from mobile robots

We present a study that examines the efficiency and usability of three different interfaces for specifying which objects should be kept private (i.e., not visible) in an office environment. Our study context is a robot “janitor” system that has the ability to blur out specified objects from its video feed. One interface is a traditional point-and-click GUI on a computer monitor, while the other two operate in the real, physical space: users either place markers on the objects to indicate privacy or use a wand tool to point at them. We compare the interfaces using both self-report (e.g., surveys) and behavioral measures. Our results showed that (1) the graphical interface performed better both in terms of time and usability, and (2) using persistent markers increased the participants ability to recall what they tagged. Choosing the right interface appears to depend on the application scenario. We also summarize feedback from the participants for improving interfaces that specify visual privacy preferences.

Using Video Manipulation to Protect Privacy in Remote Presence Systems

Remote presence systems that allow remote operators to physically move around the world, observe it, and, in some cases, manipulate it, introduce a new set of privacy concerns. Traditional telepresence systems allow remote users to passively observe, forcing them to look at whatever the camera is pointing at. If we want something to remain private, then we simply do not put it in front of the camera. Remote presence systems, on the other hand, allow active observation, and put the control of the camera in the hands of the remote operator. They can drive around, and look at the world from different viewpoints, which complicates privacy protection.

Special Issue on Open Source Software-Supported Robotics Research

Historically, robotics research has been disseminated through academic papers which lacked important implementation details, or one-time demonstrations of functionality. Neither of these methods has been conducive to either repeatable science, nor to building upon previous work. A shift is happening, however. The increasing distribution and use of open source software within robotics is moving the field to a model in which code is distributed, repeatedly executed and built upon. This cultural shift has the potential to accelerate robotics development by encouraging robust algorithms, algorithm comparison, and collaborations between research groups. Additionally, this shift should prevent new graduate students from reimplementing commonalgorithms.This special issue of Autonomous Robots is dedicated to exploring the use of open source software within a research context. Creating and disseminating usable software is timeconsuming. It involves re-writing prototype software to be