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Showing papers by "Willow Garage published in 2013"


Journal Article•DOI•
27 Feb 2013
TL;DR: A coordination structure for human-robot handovers is proposed that considers the physical and social-cognitive aspects of the interaction separately and describes how people approach, reach out their hands, and transfer objects while simultaneously coordinating the what, when, and where of handovers.
Abstract: A handover is a complex collaboration, where actors coordinate in time and space to transfer control of an object. This coordination comprises two processes: the physical process of moving to get close enough to transfer the object, and the cognitive process of exchanging information to guide the transfer. Despite this complexity, we humans are capable of performing handovers seamlessly in a wide variety of situations, even when unexpected. This suggests a common procedure that guides all handover interactions. Our goal is to codify that procedure.To that end, we first study how people hand over objects to each other in order to understand their coordination process and the signals and cues that they use and observe with their partners. Based on these studies, we propose a coordination structure for human-robot handovers that considers the physical and social-cognitive aspects of the interaction separately. This handover structure describes how people approach, reach out their hands, and transfer objects while simultaneously coordinating the what, when, and where of handovers: to agree that the handover will happen (and with what object), to establish the timing of the handover, and to decide the configuration at which the handover will occur. We experimentally evaluate human-robot handover behaviors that exploit this structure and offer design implications for seamless human-robot handover interactions.

258 citations


Proceedings Article•DOI•
24 Jun 2013
TL;DR: A novel approach to tightly integrate visual measurements with readings from an Inertial Measurement Unit (IMU) in SLAM using the powerful concept of ‘keyframes’ to maintain a bounded-sized optimization window, ensuring real-time operation.
Abstract: The fusion of visual and inertial cues has become popular in robotics due to the complementary nature of the two sensing modalities. While most fusion strategies to date rely on filtering schemes, the visual robotics community has recently turned to non-linear optimization approaches for tasks such as visual Simultaneous Localization And Mapping (SLAM), following the discovery that this comes with significant advantages in quality of performance and computational complexity. Following this trend, we present a novel approach to tightly integrate visual measurements with readings from an Inertial Measurement Unit (IMU) in SLAM. An IMU error term is integrated with the landmark reprojection error in a fully probabilistic manner, resulting to a joint non-linear cost function to be optimized. Employing the powerful concept of ‘keyframes’ we partially marginalize old states to maintain a bounded-sized optimization window, ensuring real-time operation. Comparing against both vision-only and loosely-coupled visual-inertial algorithms, our experiments confirm the benefits of tight fusion in terms of accuracy and robustness.

225 citations


Journal Article•DOI•
TL;DR: Experimental evidence shows that the proposed method can robustly estimate a camera's motion from dynamic scenes and stably track people who are moving independently or interacting.
Abstract: In this paper, we present a general framework for tracking multiple, possibly interacting, people from a mobile vision platform. To determine all of the trajectories robustly and in a 3D coordinate system, we estimate both the camera's ego-motion and the people's paths within a single coherent framework. The tracking problem is framed as finding the MAP solution of a posterior probability, and is solved using the reversible jump Markov chain Monte Carlo (RJ-MCMC) particle filtering method. We evaluate our system on challenging datasets taken from moving cameras, including an outdoor street scene video dataset, as well as an indoor RGB-D dataset collected in an office. Experimental evidence shows that the proposed method can robustly estimate a camera's motion from dynamic scenes and stably track people who are moving independently or interacting.

209 citations


Journal Article•DOI•
TL;DR: In this paper, two stochastic planners, a minimum expected risk planner and a risk-aware Markov decision process, were proposed to improve the safety and reliability of AUV operation in coastal regions.
Abstract: Recent advances in Autonomous Underwater Vehicle (AUV) technology have facilitated the collection of oceanographic data at a fraction of the cost of ship-based sampling methods. Unlike oceanographic data collection in the deep ocean, operation of AUVs in coastal regions exposes them to the risk of collision with ships and land. Such concerns are particularly prominent for slow-moving AUVs since ocean current magnitudes are often strong enough to alter the planned path significantly. Prior work using predictive ocean currents relies upon deterministic outcomes, which do not account for the uncertainty in the ocean current predictions themselves. To improve the safety and reliability of AUV operation in coastal regions, we introduce two stochastic planners: (a) a Minimum Expected Risk planner and (b) a risk-aware Markov Decision Process, both of which have the ability to utilize ocean current predictions probabilistically. We report results from extensive simulation studies in realistic ocean current fields obtained from widely used regional ocean models. Our simulations show that the proposed planners have lower collision risk than state-of-the-art methods. We present additional results from field experiments where ocean current predictions were used to plan the paths of two Slocum gliders. Field trials indicate the practical usefulness of our techniques over long-term deployments, showing them to be ideal for AUV operations.

150 citations


Journal Article•DOI•
TL;DR: Assistive mobile manipulators 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.
Abstract: 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.

143 citations


Proceedings Article•DOI•
23 Jun 2013
TL;DR: A novel method for discovering semantically grounded primitives and incrementally building and improving a finite-state representation of a task in which various contingencies can arise is introduced.
Abstract: Much recent work in robot learning from demonstration has focused on automatically segmenting continuous task demonstrations into simpler, reusable primitives. However, strong assumptions are often made about how these primitives can be sequenced, limiting the potential for data reuse. We introduce a novel method for discovering semantically grounded primitives and incrementally building and improving a finite-state representation of a task in which various contingencies can arise. Specifically, a Beta Process Autoregressive Hidden Markov Model is used to automatically segment demonstrations into motion categories, which are then further subdivided into semantically grounded states in a finite-state automaton. During replay of the task, a data-driven approach is used to collect additional data where they are most needed through interactive corrections, which are then used to improve the finite-state automaton. Together, this allows for intelligent sequencing of primitives to create novel, adaptive behavior that can be incrementally improved as needed. We demonstrate the utility of this technique on a furniture assembly task using the PR2 mobile manipulator.

121 citations


Proceedings Article•DOI•
06 May 2013
TL;DR: ROSCo is introduced, an open source system that enables expert users to construct, share, and deploy robot behaviors for home robots, and a test in the home of a person with quadriplegia, in which the person was able to automate parts of his home using previously-built behaviors.
Abstract: We introduce ROS Commander (ROSCo), an open source system that enables expert users to construct, share, and deploy robot behaviors for home robots. A user builds a behavior in the form of a Hierarchical Finite State Machine (HFSM) out of generic, parameterized building blocks, with a real robot in the develop and test loop. Once constructed, users save behaviors in an open format for direct use with robots, or for use as parts of new behaviors. When the system is deployed, a user can show the robot where to apply behaviors relative to fiducial markers (AR Tags), which allows the robot to quickly become operational in a new environment. We show evidence that the underlying state machine representation and current building blocks are capable of spanning a variety of desirable behaviors for home robots, such as opening a refrigerator door with two arms, flipping a light switch, unlocking a door, and handing an object to someone. Our experiments show that sensor-driven behaviors constructed with ROSCo can be executed in realistic home environments with success rates between 80% and 100%. We conclude by describing a test in the home of a person with quadriplegia, in which the person was able to automate parts of his home using previously-built behaviors.

81 citations


Proceedings Article•DOI•
03 Mar 2013
TL;DR: Investigating how the robotic telepresence system's height affects the local's perceptions of the operator and subsequent interactions shows that, when the system was shorter than the local and the operator was in a leadership role, the local found the operator to be less persuasive.
Abstract: A large body of research in human communication has shown that a person's height plays a key role in how persuasive, attractive, and dominant others judge the person to be. Robotic telepresence systems - systems that combine video-conferencing capabilities with robotic navigation to allow geographically dispersed people to maneuver in remote locations - represent remote users, operators, to local users, locals, through the use of an alternate physical representation. In this representation, physical characteristics such as height are dictated by the manufacturer of the system. We conducted a two-by-two (relative system height: shorter vs. taller; team role: leader vs. follower), between-participants study (n = 40) to investigate how the system's height affects the local's perceptions of the operator and subsequent interactions. Our findings show that, when the system was shorter than the local and the operator was in a leadership role, the local found the operator to be less persuasive. Furthermore, having a leadership role significantly affected the local's feelings of dominance with regard to being in control of the conversation.

77 citations


Proceedings Article•DOI•
09 Oct 2013
TL;DR: The behavior of a tendon-driven robotic gripper performing fingertip and enveloping grasps is designed, optimized and demonstrated, and an additional passive tendon can be used as a constraint preventing the gripper from entering undesirable parts of the joint workspace.
Abstract: We design, optimize and demonstrate the behavior of a tendon-driven robotic gripper performing fingertip and enveloping grasps. The gripper consists of two fingers, each with two links, and is actuated using a single active tendon. During unobstructed closing, the distal links remain parallel, creating exact fingertip grasps. Conversely, if the proximal links are stopped by contact with an object, the distal links start flexing, creating a stable enveloping grasp. We optimize the route of the active tendon and the parameters of the springs providing passive extension forces in order to achieve this behavior. We show how an additional passive tendon can be used as a constraint preventing the gripper from entering undesirable parts of the joint workspace. Finally, we introduce a method for optimizing the dimensions of the links in order to achieve enveloping grasps of a large range of objects, and apply it to a set of common household objects.

69 citations


Proceedings Article•DOI•
06 May 2013
TL;DR: This paper presents an extensible meta-algorithm that incorporates a traditional sampling-based planning algorithm with offline path shortening techniques to form an anytime algorithm which exhibits competitive solution lengths to the best known methods and optimizers.
Abstract: Recent work in sampling-based motion planning has yielded several different approaches for computing good quality paths in high degree of freedom systems: path shortcutting methods that attempt to shorten a single solution path by connecting non-consecutive configurations, a path hybridization technique that combines portions of two or more solutions to form a shorter path, and asymptotically optimal algorithms that converge to the shortest path over time. This paper presents an extensible meta-algorithm that incorporates a traditional sampling-based planning algorithm with offline path shortening techniques to form an anytime algorithm which exhibits competitive solution lengths to the best known methods and optimizers. A series of experiments involving rigid motion and complex manipulation are performed as well as a comparison with asymptotically optimal methods which show the efficacy of the proposed scheme, particularly in high-dimensional spaces.

65 citations


Book Chapter•DOI•
01 Jan 2013
TL;DR: A simple extension to the RRT algorithm to search the combined space of robot and objects and an implementation of DARRT, a sampling-based algorithm for planning with multiple types of manipulation, are described.
Abstract: We present DARRT, a sampling-based algorithm for planning with multiple types of manipulation. Given a robot, a set of movable objects, and a set of actions for manipulating the objects, DARRT returns a sequence of manipulation actions that move the robot and objects from an initial configuration to a final configuration. The manipulation actions may be non-prehensile,meaning that the object is not rigidly attached to the robot, such as push, tilt, or pull. We describe a simple extension to the RRT algorithm to search the combined space of robot and objects and present an implementation of DARRT on the Willow Garage PR2 robot.

Proceedings Article•DOI•
27 Apr 2013
TL;DR: It is found that physical embodiment and control by the local user increased the amount of trust built between partners, suggesting that both physical embodied and control of the system influence interpersonal trust in mediated communication and have implications for future system designs.
Abstract: Communication technologies are becoming increasingly diverse in form and functionality, making it important to identify which aspects of these technologies actually improve geographically distributed communication. Our study examines two potentially important aspects of communication technologies which appear in robot-mediated communication - physical embodiment and control of this embodiment. We studied the impact of physical embodiment and control upon interpersonal trust in a controlled laboratory experiment using three different videoconferencing settings: (1) a handheld tablet controlled by a local user, (2) an embodied system controlled by a local user, and (3) an embodied system controlled by a remote user (n = 29 dyads). We found that physical embodiment and control by the local user increased the amount of trust built between partners. These results suggest that both physical embodiment and control of the system influence interpersonal trust in mediated communication and have implications for future system designs.

Proceedings Article•DOI•
Ilya Lysenkov, Vincent Rabaud1•
06 May 2013
TL;DR: A new algorithm for recognition and pose estimation of rigid transparent objects which can deal with overlapping instances and cluttered environments is proposed and is evaluated on a Microsoft Kinect and also on a PR2 robot.
Abstract: Transparent objects are ubiquitous in human environments but, due to their special interaction with light, very few vision methods exist to identify them. We propose a new algorithm for recognition and pose estimation of rigid transparent objects which can deal with overlapping instances and cluttered environments. Using an active depth sensor for segmentation of the objects and 2d edge analysis for pose estimation, we are able to provide accurate identification and position. The proposed method is evaluated on a Microsoft Kinect and also on a PR2 robot. Results show that the algorithm is robust and accurate enough for robotic grasping and that it can be used in practical applications like table cleaning.

Proceedings Article•DOI•
Maya Cakmak1, Leila Takayama1•
03 Mar 2013
TL;DR: An analysis of household chore lists is presented with an eye towards building a comprehensive tasks lists for domestic robots and the necessity for end-user programming of domestic robots at different levels is discussed.
Abstract: We present an analysis of household chore lists with an eye towards building a comprehensive tasks lists for domestic robots. We identify the common structures of cleaning and organizing tasks, and characterize properties of their targets. Based on this analysis, we discuss the necessity for end-user programming of domestic robots at different levels.

Patent•
07 Mar 2013
TL;DR: In this paper, the authors present a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution.
Abstract: One embodiment is directed to a system for presenting views of a very large point data set, comprising: a storage system comprising data representing a point cloud comprising a very large number of associated points; a controller operatively coupled to the storage cluster and configured to automatically and deterministically organize the point data into an octree hierarchy of data sectors, each of which is representative of one or more of the points at a given octree mesh resolution; and a user interface through which a user may select a viewing perspective origin and vector, which may be utilized to command the controller to assemble an image based at least in part upon the selected origin and vector, the image comprising a plurality of data sectors pulled from the octree hierarchy

Proceedings Article•DOI•
27 Apr 2013
TL;DR: The evidence-based design and evaluation of a novel tool for community leaders, Community Insights (CI), provides actionable analytics that help community leaders foster healthy communities, providing value to both members and the organization.
Abstract: Online communities are increasingly being deployed in enterprises to increase productivity and share expertise. Community leaders are critical for fostering successful communities, but existing technologies rarely support leaders directly, both because of a lack of clear data about leader needs, and because existing tools are member- rather than leader-centric. We present the evidence-based design and evaluation of a novel tool for community leaders, Community Insights (CI). CI provides actionable analytics that help community leaders foster healthy communities, providing value to both members and the organization. We describe empirical and system contributions derived from a long-term deployment of CI to leaders of 470 communities over 10 months. Empirical contributions include new data showing: (a) which metrics are most useful for leaders to assess community health, (b) the need for and how to design actionable metrics, (c) the need for and how to design contextualized analytics to support sensemaking about community data. These findings motivate a novel community system that provides leaders with useful, actionable and contextualized analytics.

Proceedings Article•DOI•
06 May 2013
TL;DR: This paper presents two novel techniques to accelerate the computation of broad-phase data structures: a progressive technique that incrementally computes a high-quality dynamic AABB tree for fast culling and an octree representation of the point cloud data as a proximity data structure.
Abstract: Most prior techniques for proximity computations are designed for synthetic models and assume exact geometric representations. However, real robots construct representations of the environment using their sensors, and the generated representations are more cluttered and less precise than synthetic models. Furthermore, this sensor data is updated at high frequency. In this paper, we present new collision- and distance-query algorithms, which can efficiently handle large amounts of point cloud sensor data received at real-time rates. We present two novel techniques to accelerate the computation of broad-phase data structures: 1) we present a progressive technique that incrementally computes a high-quality dynamic AABB tree for fast culling, and 2) we directly use an octree representation of the point cloud data as a proximity data structure. We assign a probability value to each leaf node of the tree, and the algorithm computes the nodes corresponding to high collision probability. In practice, our new approaches can be an order of magnitude faster than previous methods. We demonstrate the performance of the new methods on both synthetic data and on sensor data collected using a Kinectâ„¢ for motion planning for a mobile manipulator robot.

Book Chapter•DOI•
09 Sep 2013
TL;DR: This paper proposes to use human detections as cues to more accurately estimate the vanishing points of highly cluttered indoor scenes, and shows that this approach improves 3D interpretation of scenes.
Abstract: Recovering the spatial layout of cluttered indoor scenes is a challenging problem. Current methods generate layout hypotheses from vanishing point estimates produced using 2D image features. This method fails in highly cluttered scenes in which most of the image features come from clutter instead of the room’s geometric structure. In this paper, we propose to use human detections as cues to more accurately estimate the vanishing points. Our method is built on top of the fact that people are often the focus of indoor scenes, and that the scene and the people within the scene should have consistent geometric configurations in 3D space. We contribute a new data set of highly cluttered indoor scenes containing people, on which we provide baselines and evaluate our method. This evaluation shows that our approach improves 3D interpretation of scenes.

Book Chapter•DOI•
01 Jan 2013
TL;DR: This work presents fast and novel algorithms to perform k-NN (k-nearest neighbor) queries in high dimensional configuration spaces based on locality-sensitive hashing and derive tight bounds on their accuracy.
Abstract: We present a novel approach to improve the performance of sample-based motion planners by learning from prior instances. Our formulation stores the results of prior collision and local planning queries. This information is used to accelerate the performance of planners based on probabilistic collision checking, select new local paths in free space, and compute an efficient order to perform queries along a search path in a graph. We present fast and novel algorithms to perform k-NN (k-nearest neighbor) queries in high dimensional configuration spaces based on locality-sensitive hashing and derive tight bounds on their accuracy. The k-NN queries are used to perform instance-based learning and have a sub-linear time complexity. Our approach is general, makes no assumption about the sampling scheme, and can be used with various sample-based motion planners, including PRM, Lazy-PRM, RRT and RRT*, by making small changes to these planners.We observe up to 100% improvement in the performance of various planners on rigid and articulated robots.

Proceedings Article•DOI•
23 Jun 2013
TL;DR: In this paper, the authors proposed a framework of planning with experience graphs which encode and reuse previous experiences for constrained manipulation tasks, e.g., door opening and drawer opening, where the motion of the object itself involves only a single degree of freedom.
Abstract: Motion planning in high dimensional state spaces, such as for mobile manipulation, is a challenging problem. Constrained manipulation, e.g., opening articulated objects like doors or drawers, is also hard since sampling states on the constrained manifold is expensive. Further, planning for such tasks requires a combination of planning in free space for reaching a desired grasp or contact location followed by planning for the constrained manipulation motion, often necessitating a slow two step process in traditional approaches. In this work, we show that combined planning for such tasks can be dramatically accelerated by providing user demonstrations of the constrained manipulation motions. In particular, we show how such demonstrations can be incorporated into a recently developed framework of planning with experience graphs which encode and reuse previous experiences. We focus on tasks involving articulation constraints, e.g., door opening or drawer opening, where the motion of the object itself involves only a single degree of freedom. We provide experimental results with the PR2 robot opening a variety of such articulated objects using our approach, using full-body manipulation (after receiving kinesthetic demonstrations). We also provide simulated results highlighting the benefits of our approach for constrained manipulation tasks.

Proceedings Article•DOI•
03 Mar 2013
TL;DR: This study explores the effects of visual feedback for remote teleoperators, using a controlled experiment in which mirrors were either present or absent in the local room with the MRP system and compared to mirrors-absent participants, mirrors-present participants were more visible on the MRp screens and practiced navigating longer.
Abstract: Mobile remote presence systems present new opportunities and challenges for physically distributed people to meet and work together. One of the challenges observed from a couple of years of using Texai, a mobile remote presence (MRP) system, is that remote operators are often unaware of how they present themselves through the MRP. Problems arise when remote operators are not clearly visible through the MRP video display; this mistake makes the MRP operators look like anonymous intruders into the local space rather than approachable colleagues. To address this problem, this study explores the effects of visual feedback for remote teleoperators, using a controlled experiment in which mirrors were either present or absent in the local room with the MRP system (N=24). Participants engaged in a warm-up remote communication task followed by a remote driving task. Compared to mirrors-absent participants, mirrors-present participants were more visible on the MRP screens and practiced navigating longer. However, the mirrors-present participants also reported experiencing more frustration and having less fun. Implications for theory and design are discussed.

Proceedings Article•DOI•
21 Jul 2013
TL;DR: NuttyTracks is a symbolic real-time animation system for animating any robotic character using animation tools commonly used by professional animators.
Abstract: NuttyTracks is a symbolic real-time animation system for animating any robotic character using animation tools commonly used by professional animators. Our system brings artists and programmers closer to each other in the quest for creating the illusion of life in robotic characters.

Proceedings Article•DOI•
01 Oct 2013
TL;DR: CAT is introduced, a constraint-aware teleoperation method that can track continuously updating 6-DOF end-effector goals while avoiding environment collisions, self-collisions, and joint limits.
Abstract: We introduce CAT, a constraint-aware teleoperation method that can track continuously updating 6-DOF end-effector goals while avoiding environment collisions, self-collisions, and joint limits. Our method uses sequential quadratic programming to generate motion trajectories that obey kinematic constraints while attempting to reduce the distance to the goal with each step. Environment models are created and updated at run-time using a commodity depth camera. We compare our method to three additional teleoperation strategies, based on global motion planning, inverse kinematics, and Jacobian-transpose control. Our analysis, using a real robot in a variety of scenes, highlights the strengths of each method, and shows that the CAT method we introduce performs well over a wide range of scenarios.

Proceedings Article•DOI•
06 May 2013
TL;DR: This work extends planning with Experience Graphs to work in an anytime fashion so a first solution is found quickly using prior experience so that the dependence on this experience is reduced in order to produce closer to optimal solutions.
Abstract: Robots operating in real world environments need to find motion plans quickly. Robot motion should also be efficient and, when operating among people, predictable. Minimizing a cost function, e.g. path length, can produce short, reasonable paths. Anytime planners are ideal for this since they find an initial solution quickly and then improve solution quality as time permits. In previous work, we introduced the concept of Experience Graphs, which allow search-based planners to find paths with bounded sub-optimality quickly by reusing parts of previous paths where relevant. Here we extend planning with Experience Graphs to work in an anytime fashion so a first solution is found quickly using prior experience. As time allows, the dependence on this experience is reduced in order to produce closer to optimal solutions. We also demonstrate how Experience Graphs provide a new way of approaching incremental planning as they naturally reuse information when the environment, the starting configuration of the robot or the goal configuration change. Experimentally, we demonstrate the anytime and incremental properties of our algorithm on mobile manipulation tasks in both simulation and on a real PR2 robot.

Journal Article•DOI•
TL;DR: LiveAction as mentioned in this paper is a fully-automated approach to generate task models from Web usage data, which can be used to populate the task model repositories required by many automation systems, helping us take advantage of automation in our everyday lives.
Abstract: Task automation systems promise to increase human productivity by assisting us with our mundane and difficult tasks. These systems often rely on people to (1) identify the tasks they want automated and (2) specify the procedural steps necessary to accomplish those tasks (i.e., to create task models). However, our interviews with users of a Web task automation system reveal that people find it difficult to identify tasks to automate and most do not even believe they perform repetitive tasks worthy of automation. Furthermore, even when automatable tasks are identified, the well-recognized difficulties of specifying task steps often prevent people from taking advantage of these automation systems.In this research, we analyze real Web usage data and find that people do in fact repeat behaviors on the Web and that automating these behaviors, regardless of their complexity, would reduce the overall number of actions people need to perform when completing their tasks, potentially saving time. Motivated by these findings, we developed LiveAction, a fully-automated approach to generating task models from Web usage data. LiveAction models can be used to populate the task model repositories required by many automation systems, helping us take advantage of automation in our everyday lives.

Proceedings Article•DOI•
06 May 2013
TL;DR: This work presents a planning framework that handles non-spring and spring-loaded doors, in cluttered or confined workspaces, planning the approach to the door, pushing or pulling it open, and passing through, and yields an overall least-cost path.
Abstract: Opening and navigating through doors remains a challenging problem, particularly in cluttered environments and for spring-loaded doors. Passing through doors, especially spring-loaded doors, requires making and breaking contacts with the door and preventing the door from closing while passing through. In this work, we present a planning framework that handles non-spring and spring-loaded doors, in cluttered or confined workspaces, planning the approach to the door, pushing or pulling it open, and passing through. Because the problem is solved in a combined search space, the planner yields an overall least-cost path. The planner is able to insert a transition between robot-door contacts at any point along the plan. We utilize a compact graph-based representation of the problem to keep planning times low. We precompute the force workspace of the end-effectors to eliminate checks against joint torque limits at plan time. We have validated our solution in both simulation and real-world experiments on the PR2 mobile manipulation platform; the robot is able to successfully open a variety of spring-loaded and non-spring-loaded doors by pushing and pulling.

Journal Article•DOI•
TL;DR: Haptic assistance in combination with auditory feedback instead of visual feedback is investigated, implying that users of graphical user interfaces could similarly benefit from force-sensitive detents and more generally real-time regulation of the strength of haptic assistance.
Abstract: Haptic technology, providing force cues and creating a programmable interface, can assist users in more accurately using an interface. This paper investigates haptic assistance in combination with auditory feedback instead of visual feedback. A user test is carried out in which participants select fundamental frequencies from a continuous range to play brief musical melodies. Two control conditions are compared with two detent-based haptic assistance conditions. The detents gently guide the users toward locations of equal tempered fundamental frequencies. Results from the user test confirm improved accuracy brought about by the detents. It is further helpful to provide regulation of the strength of haptic assistance in real time, allowing the user to remain always in control. This concept motivated the force-sensitive detent condition, which enables the user to adjust the strength of the haptic assistance in real time by changing the downward force applied to the haptic device. The work implies that users of graphical user interfaces could similarly benefit from force-sensitive detents and more generally real-time regulation of the strength of haptic assistance.

Proceedings Article•DOI•
Mihai Pomarlan, Ioan A. Sucan1•
01 Nov 2013
TL;DR: A method to efficiently compute global motion plans for robotic manipulators in dynamically changing environments by constructing a sparse roadmap to approximate the configuration space of the manipulator in an empty environment is introduced.
Abstract: This paper introduces a method to efficiently compute global motion plans for robotic manipulators in dynamically changing environments. An offline computation step is used to construct a sparse roadmap to approximate the configuration space of the manipulator in an empty environment. When the robot is running, a representation of the environment to keep track of the robot's free workspace is maintained as sensor updates are received. The maintained representation of the free workspace is used in conjunction with the data computed offline to quickly compute good quality global motion plans.

Proceedings Article•DOI•
07 Nov 2013
TL;DR: Several sensors, including a 3-D camera, low- cost laser rangefinders, sonar sensors and a low-cost inertial measurement unit, were considered for use on a smart wheelchair.
Abstract: The success of smart wheelchairs in practice will depend on achieving sensing that is both highly reliable and low cost. Recent options, made in volume for gaming and for hobbyists, offer such a possibility. Several sensors, including a 3-D camera, low-cost laser rangefinders, sonar sensors and a low-cost inertial measurement unit, were considered for use on a smart wheelchair. Encouraging performance results are reported.

Proceedings Article•DOI•
24 Jun 2013
TL;DR: The pros and cons of the interfaces, the engagement of visitors at the exhibit, and the lessons for other exhibitors who aim to achieve active prolonged engagement with robots in museum settings are presented.
Abstract: We describe our experience exhibiting a human-size robot in a museum, encouraging visitors to interact with the robot and even program it to perform a sequence of timed poses. At the museum, users' programs were run on a real robot for all to see. The installation attracted and engaged visitors from age two to adult. The most intuitive of our interfaces was equally captivating for young and older visitors. We present the pros and cons of our interfaces and the engagement of visitors at the exhibit as lessons for other exhibitors who aim to achieve active prolonged engagement with robots in museum settings.