4 citations · 11 across the 12 of their papers we have counts for
15 papers
Planning Coordinated Human-Robot Motions with Neural Network Full-Body Prediction Models
Philipp Kratzer, Marc Toussaint, Jim Mainprice
Numerical optimization has become a popular approach to plan smooth motion trajectories for robots. However, when sharing space with humans, balancing properly safety, comfort and…
Learning to Arbitrate Human and Robot Control using Disagreement between Sub-Policies
Yoojin Oh, Marc Toussaint, Jim Mainprice
In the context of teleoperation, arbitration refers to deciding how to blend between human and autonomous robot commands. We present a reinforcement learning solution that learns a…
GraspME -- Grasp Manifold Estimator
Janik Hager, Ruben Bauer, Marc Toussaint +1
In this paper, we introduce a Grasp Manifold Estimator (GraspME) to detect grasp affordances for objects directly in 2D camera images. To perform manipulation tasks autonomously it…
A System for Traded Control Teleoperation of Manipulation Tasks using Intent Prediction from Hand Gestures
Yoojin Oh, Marc Toussaint, Jim Mainprice
This paper presents a teleoperation system that includes robot perception and intent prediction from hand gestures. The perception module identifies the objects present in the robo…
Hierarchical Human-Motion Prediction and Logic-Geometric Programming for Minimal Interference Human-Robot Tasks
An T. Le, Philipp Kratzer, Simon Hagenmayer +2
In this paper, we tackle the problem of human-robot coordination in sequences of manipulation tasks. Our approach integrates hierarchical human motion prediction with Task and Moti…
MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze
Philipp Kratzer, Simon Bihlmaier, Niteesh Balachandra Midlagajni +3
As robots become more present in open human environments, it will become crucial for robotic systems to understand and predict human motion. Such capabilities depend heavily on the…
Natural Gradient Shared Control
Yoojin Oh, Shao-Wen Wu, Marc Toussaint +1
We propose a formalism for shared control, which is the problem of defining a policy that blends user control and autonomous control. The challenge posed by the shared autonomy sys…
An Interior Point Method Solving Motion Planning Problems with Narrow Passages
Jim Mainprice, Nathan Ratliff, Marc Toussaint +1
Algorithmic solutions for the motion planning problem have been investigated for five decades. Since the development of A* in 1969 many approaches have been investigated, tradition…
Anticipating Human Intention for Full-Body Motion Prediction in Object Grasping and Placing Tasks
Philipp Kratzer, Niteesh Balachandra Midlagajni, Marc Toussaint +1
Motion prediction in unstructured environments is a difficult problem and is essential for safe and efficient human-robot space sharing and collaboration. In this work, we focus on…
Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks
Philipp Kratzer, Marc Toussaint, Jim Mainprice
Human movement prediction is difficult as humans naturally exhibit complex behaviors that can change drastically from one environment to the next. In order to alleviate this issue,…
Learning Arbitration for Shared Autonomy by Hindsight Data Aggregation
Yoojin Oh, Marc Toussaint, Jim Mainprice
In this paper we present a framework for the teleoperation of pick-and-place tasks. We define a shared control policy that allows to blend between direct user control and autonomou…
Motion Prediction with Recurrent Neural Network Dynamical Models and Trajectory Optimization
Philipp Kratzer, Marc Toussaint, Jim Mainprice
Predicting human motion in unstructured and dynamic environments is difficult as humans naturally exhibit complex behaviors that can change drastically from one environment to the…
Learning Sensory-Motor Associations from Demonstration
Vincent Berenz, Ahmed Bjelic, Lahiru Herath +1
We propose a method which generates reactive robot behavior learned from human demonstration. In order to do so, we use the Playful programming language which is based on the react…
Real-time Perception meets Reactive Motion Generation
Daniel Kappler, Franziska Meier, Jan Issac +7
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-pred…
Goal Set Inverse Optimal Control and Iterative Re-planning for Predicting Human Reaching Motions in Shared Workspaces
Jim Mainprice, Rafi Hayne, Dmitry Berenson
To enable safe and efficient human-robot collaboration in shared workspaces it is important for the robot to predict how a human will move when performing a task. While predicting…