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We formalize the problem of adapting a demonstrated trajectory to a new start and goal configuration as an optimization problem over a Hilbert space of trajectories: minimize the distance between the demonstration and the new trajectory subject to the new end point constraints. We show that the commonly used version of Dynamic Movement Primitives (DMPs) implement this minimization in the way they...
In this work we present a fast kinodynamic RRT-planner that uses dynamic nonprehensile actions to rearrange cluttered environments. In contrast to many previous works, the presented planner is not restricted to quasi-static interactions and monotonicity. Instead the results of dynamic robot actions are predicted using a black box physics model. Given a general set of primitive actions and a physics...
Rapidly-exploring random trees (RRTs) are popular in motion planning because they find solutions efficiently to single-query problems. Optimal RRTs (RRT*s) extend RRTs to the problem of finding the optimal solution, but in doing so asymptotically find the optimal path from the initial state to every state in the planning domain. This behaviour is not only inefficient but also inconsistent with their...
In Spring 2014, the Personal Robotics Lab at CMU collaborated with the School of Drama to develop, produce and stage a live theatrical performance at the Purnell Center for the Arts in Pittsburgh. This paper describes some of our unique experiences collaborating with drama faculty, the director and the actor. We highlight the challenges arising from theatrical performance and specifically describe...
Good communication is critical to seamless human-robot interaction. Among numerous communication channels, here we focus on gestures, and in particular on spacial deixis: pointing at objects in the environment in order to reference them. We propose a mathematical model that enables robots to generate pointing configurations that make the goal object as clear as possible — pointing configurations that...
Functional gradient algorithms (e.g. CHOMP) have recently shown great promise for producing locally optimal motion for complex many degree-of-freedom robots. A key limitation of such algorithms is the difficulty in incorporating constraints and cost functions that explicitly depend on time. We present T-CHOMP, a functional gradient algorithm that overcomes this limitation by directly optimizing in...
“In-hand manipulation” is the ability to reposition an object in the hand, for example when adjusting the grasp of a hammer before hammering a nail. The common approach to in-hand manipulation with robotic hands, known as dexterous manipulation [1], is to hold an object within the fingertips of the hand and wiggle the fingers, or walk them along the object's surface. Dexterous manipulation, however,...
We investigate the problem of a robot searching for an object. This requires reasoning about both perception and manipulation: some objects are moved because the target may be hidden behind them, while others are moved because they block the manipulator’s access to other objects. We contribute a formulation of the object search by manipulation problem using visibility and accessibility relations between...
We investigate the problem of estimating the state of an object during manipulation. Contact sensors provide valuable information about the object state during actions which involve persistent contact, e.g. pushing. However, contact sensing is very discriminative by nature, and therefore the set of object states that contact a sensor constitutes a lower-dimensional manifold in the state space of the...
In this paper, we consider the problem of Lifelong Robotic Object Discovery (LROD) as the long-term goal of discovering novel objects in the environment while the robot operates, for as long as the robot operates. As a first step towards LROD, we automatically process the raw video stream of an entire workday of a robotic agent to discover objects. We claim that the key to achieve this goal is to...
Many robotic systems deal with uncertainty by performing a sequence of information gathering actions. In this work, we focus on the problem of efficiently constructing such a sequence by drawing an explicit connection to submodularity. Ideally, we would like a method that finds the optimal sequence, taking the minimum amount of time while providing sufficient information. Finding this sequence, however,...
We investigate the problem of a robot searching for an object. This requires reasoning about both perception and manipulation: certain objects are moved because the target may be hidden behind them and others are moved because they block the manipulator's access to other objects. We contribute a formulation of the object search by manipulation problem using visibility and accessibility relations between...
Autonomous manipulation has made tremendous progress in recent years, leveraging new algorithms and capabilities of mobile manipulators to address complex human environments. However, most current systems inadequately address one key feature of human environments: that they are populated with humans. What would it take for a human and robot to prepare a meal together in a kitchen, or to assemble a...
A key requirement for seamless human-robot collaboration is for the robot to make its intentions clear to its human collaborator. A collaborative robot's motion must be legible, or intent-expressive. Legibility is often described in the literature as and effect of predictable, unsurprising, or expected motion. Our central insight is that predictability and legibility are fundamentally different and...
In assistive teleoperation, the robot provides assistance by predicting the user's intent. Prior work has focused on improving prediction by adapting it to the user's behavior. In this work, we investigate adaptation in the opposite direction: training the user's behavior to the prediction. Results from our user study suggest that users can significantly improve the performance of a simple static...
Overall across the data, the more capable robot had a significantly higher rating (M = 3.21; SD = 1.31) than the less capable (M = 2.98; SD = 1.29); t(312) = 3.77; p < 0.001.
During operation of robots large amounts of data are produced and processed for instance in perception, actuation, or decision making. Nowadays this data is typically volatile and disposed right after use. But this data can be valuable and useful later. Therefore we propose a database system that taps into common robot middleware to record any and all data produced at run-time. We present two examples...
When performing physical collaboration tasks, like packing a picnic basket together, humans communicate strongly and often subtly via multiple channels like gaze, speech, gestures, movement and posture. Understanding and participating in this communication enables us to predict a physical action rather than react to it, producing seamless collaboration. In this paper, we automatically learn key discriminative...
In teleoperation, the user's input is mapped onto the robot via a motion retargetting function. This function must differ between robots because of their different kinematics, between users because of their different preferences, and even between tasks that the users perform with the robot. Our work enables users to customize this retargetting function, and achieve any of these required differences...
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