Willow Garage

About: Willow Garage is a based out in . It is known for research contribution in the topics: Robot & Mobile robot. The organization has 76 authors who have published 191 publications receiving 28617 citations.

Making technology homey: finding sources of satisfaction and meaning in home automation

Abstract: Home and automation are not natural partners--one homey and the other cold. Most current automation in the home is packaged in the form of appliances. To better understand the current reality and possible future of living with other types of domestic technology, we went out into the field to conduct need finding interviews among people who have already introduced automation into their homes and kept it there--home automators. We present the lessons learned from these home automators as frameworks and implications for the values that domestic technology should support. In particular, we focus on the satisfaction and meaning that the home automators derived from their projects, especially in connecting to their homes (rather than simply controlling their homes). These results point the way toward other technologies designed for our everyday lives at home.

Mobile Manipulation in Unstructured Environments: Perception, Planning, and Execution

Abstract: Unstructured human environments present a substantial challenge to effective robotic operation. Mobile manipulation in human environments requires dealing with novel unknown objects, cluttered workspaces, and noisy sensor data. We present an approach to mobile pick and place in such environments using a combination of two-dimensional (2-D) and three-dimensional (3-D) visual processing, tactile and proprioceptive sensor data, fast motion planning, reactive control and monitoring, and reactive grasping. We demonstrate our approach by using a two-arm mobile manipulation system to pick and place objects. Reactive components allow our system to account for uncertainty arising from noisy sensors, inaccurate perception (e.g., object detection or registration), or dynamic changes in the environment. We also present a set of tools that allows our system to be easily configured within a short time for a new robotic system.

Task-driven Tactile Exploration

Abstract: This paper presents a decision-theoretic approach to problems that require accurate placement of a robot relative to an object in the world, including grasping and insertion. The decision process is applied to a robot hand with tactile sensors, to localize the object and ultimately achieve a target placement by selecting among grasping and information-gathering trajectories. The process is demonstrated in simulation and on a real robot.

Bodies in motion: mobility, presence, and task awareness in telepresence

Abstract: Robotic telepresence systems - videoconferencing systems that allow a remote user to drive around in another location - provide an alternative to video-mediated communications as a way of interacting over distances. These systems, which are seeing increasing use in business and medical settings, are unique in their ability to grant the remote user the ability to maneuver in a distant location. While this mobility promises increased feelings of "being there" for remote users and thus greater support for task collaboration, whether these promises are borne out, providing benefits in task performance, is unknown. To better understand the role that mobility plays in shaping the remote user's sense of presence and its potential benefits, we conducted a two-by-two (system mobility: stationary vs. mobile; task demands for mobility: low vs. high) controlled laboratory experiment. We asked participants (N=40) to collaborate in a construction task with a confederate via a robotic telepresence system. Our results showed that mobility significantly increased the remote user's feelings of presence, particularly in tasks with high mobility requirements, but decreased task performance. Our findings highlight the positive effects of mobility on feelings of "being there," while illustrating the need to design support for effective use of mobility in high-mobility tasks.

E-Graphs: Bootstrapping Planning with Experience Graphs

Abstract: Human environments possess a significant amount of underlying structure that is under-utilized in motion planning and mobile manipulation In domestic environments for example, walls and shelves are static, large objects such as furniture and kitchen appliances most of the time do not move and do not change, and objects are typically placed on a limited number of support surfaces such as tables, countertops or shelves Motion planning for robots operating in such environments should be able to exploit this structure to improve its performance with each execution of a task In this paper, we develop an online motion planning approach which learns from its planning episodes (experiences) a graph, an Experience Graph This graph represents the underlying connectivity of the space required for the execution of the mundane tasks performed by the robot The planner uses the Experience graph to accelerate its planning efforts whenever possible On the theoretical side, we show that planning with Experience graphs is complete and provides bounds on sub-optimality with respect to the graph that represents the original planning problem On the experimental side, we show in simulations and on a physical robot that our approach is particularly suitable for higher-dimensional motion planning tasks such as planning for single-arm manipulation and two armed mobile manipulation The approach provides significant speedups over planning from scratch and generates predictable motion plans: motions planned from start positions that are close to each other to goal positions that are also close to each other tend to be similar In addition, we show how the Experience graphs can incorporate solutions from other approaches such as human demonstrations, providing an easy way of bootstrapping motion planning for complex tasks