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Goal Set Inverse Optimal Control and Iterative Re-planning for Predicting Human Reaching Motions in Shared Workspaces [article]

Jim Mainprice and Rafi Hayne and Dmitry Berenson
2016 arXiv   pre-print
We also show that our method outperforms baselines for predicting human motion when a human and a robot share the workspace.  ...  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.  ...  The approach, based on Inverse Optimal Control (IOC) and Goal Set Iterative replanning allows us to find a cost function balancing different features that outperforms hand-tuning of the cost function in  ... 
arXiv:1606.02111v1 fatcat:adk7hwvfabekpf2dzf65jpnkeq

Predicting human reaching motion in collaborative tasks using Inverse Optimal Control and iterative re-planning

Jim Mainprice, Rafi Hayne, Dmitry Berenson
2015 2015 IEEE International Conference on Robotics and Automation (ICRA)  
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 human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing  ...  Predicting Human Reaching Motion in Collaborative Tasks Using Inverse Optimal Control and Iterative Re-planning Abstract-To enable safe and efficient human-robot collaboration in shared workspaces, it  ... 
doi:10.1109/icra.2015.7139282 dblp:conf/icra/MainpriceHB15 fatcat:55c6e7shlfckbe7c42z7luoama

Hierarchical Human-Motion Prediction and Logic-Geometric Programming for Minimal Interference Human-Robot Tasks [article]

An T. Le, Philipp Kratzer, Simon Hagenmayer, Marc Toussaint, Jim Mainprice
2021 arXiv   pre-print
Our version of Dynamic LGP, replans periodically to handle the mismatch between the human motion prediction and the actual human behavior.  ...  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 Motion Planning (TAMP).  ...  The authors thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Philipp Kratzer.  ... 
arXiv:2104.08137v2 fatcat:fy2zvplcpvbgxf3ch46s2xga6q

Continuous Motion Planning for Service Robots with Multiresolution in Time [chapter]

Ricarda Steffens, Matthias Nieuwenhuisen, Sven Behnke
2015 Advances in Intelligent Systems and Computing  
Our approach is based on stochastic trajectory optimization for motion planning (STOMP) and designed to decrease the optimization time in order to enable frequent replanning.  ...  In addition to employing temporal multiresolution, we speed up trajectory optimization by initializing replanning with the previous plan.  ...  The minimum number of iterations is set to 19 for this experiment.  ... 
doi:10.1007/978-3-319-08338-4_16 fatcat:ypfirlal6rai3pvwpuo4orwghi

An Efficient Online Trajectory Generation Method Based on Kinodynamic Path Search and Trajectory Optimization for Human-Robot Interaction Safety

Hongyan Liu, Daokui Qu, Fang Xu, Zhenjun Du, Kai Jia, Mingmin Liu
2022 Entropy  
With the rapid development of robot perception and planning technology, robots are gradually getting rid of fixed fences and working closely with humans in shared workspaces.  ...  The safety of human-robot coexistence has become critical. Traditional motion planning methods perform poorly in dynamic environments where obstacles motion is highly uncertain.  ...  In these applications, robots act as human partners, with side-by-side or face-to-face working with humans in shared workspaces to complete specific tasks, and the safety issue of human-robot coexistence  ... 
doi:10.3390/e24050653 fatcat:gv3izev2kjbbxao4w442nsfup4

Human-Aware Robotic Assistant for Collaborative Assembly: Integrating Human Motion Prediction With Planning in Time

Vaibhav V. Unhelkar, Przemyslaw A. Lasota, Quirin Tyroller, Rares-Darius Buhai, Laurie Marceau, Barbara Deml, Julie A. Shah
2018 IEEE Robotics and Automation Letters  
For instance, researchers have developed techniques utilizing inverse optimal control [19] and Bayesian classification [20] to generate motion predictors using labeled data of arm motion.  ...  One such approach leverages the assumption that people move in an efficient manner while navigating an environment in order to model human motions using maximum entropy inverse optimal control [24] .  ... 
doi:10.1109/lra.2018.2812906 dblp:journals/ral/UnhelkarLTBMDS18 fatcat:z5jpofexgbfzrobiadxqdhxnvq

Introduction to the Special Issue on Movement Science for Humans and Humanoids

Dana Kulic, Gentiane Venture, Katsu Yamane, Emel Demircan, Katja Mombaur
2016 IEEE Transactions on robotics  
in humanoid robotics, and human motor control.  ...  His research interests include humanoid robot control and motion synthesis, physical human-robot interaction, character animation, and human motion simulation. Dr.  ...  The paper "Goal Set Inverse Optimal Control and Iterative Replanning for Predicting Human Reaching Motions in Shared Workspaces," by Jim Mainprice, Rafi Hayne, and Dmitry Berenson, develops an approach  ... 
doi:10.1109/tro.2016.2593807 fatcat:nkz7uw3s5re3rg3qtnga7y3yjy

Workspace monitoring and planning for safe mobile manipulation [article]

Christian Frese, Angelika Zube, Christian Frey
2020 arXiv   pre-print
By integrating the monitoring, planning, and interaction control components, the task of grasping, placing and delivering objects to humans in a shared workspace is demonstrated.  ...  In order to enable physical human-robot interaction where humans and (mobile) manipulators share their workspace and work together, robots have to be equipped with important capabilities to guarantee human  ...  Acknowledgement The presented research has been supported by the European Commission's 7th Framework Programme as part of the project SAPHARI (Safe and Autonomous Physical Human-Aware Robot Interaction  ... 
arXiv:2006.01546v1 fatcat:idpwi23ujnhbtgozo26vvhl4gm

Map-Predictive Motion Planning in Unknown Environments [article]

Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone
2019 arXiv   pre-print
We present a unified method that combines map prediction and motion planning for safe, time-efficient autonomous navigation of unknown environments by dynamically-constrained robots.  ...  Algorithms for motion planning in unknown environments are generally limited in their ability to reason about the structure of the unobserved environment.  ...  States and controls share the same subscript convention.  ... 
arXiv:1910.08184v1 fatcat:d7sp36s3f5ab7itp6mp2savbx4

Multi 3D camera mapping for predictive and reflexive robot manipulator trajectory estimation

Justinas Miseikis, Kyrre Glette, Ole Jakob Elle, Jim Torresen
2016 2016 IEEE Symposium Series on Computational Intelligence (SSCI)  
The main goal of our work is to make the operation more flexible in unstructured dynamic workspaces and not just avoid obstacles, but also adapt when performing collaborative tasks with humans in the near  ...  We present a method combining 3D Camera based workspace mapping, and a predictive and reflexive robot manipulator trajectory estimation to allow more efficient and safer operation in dynamic workspaces  ...  ACKNOWLEDGMENT This work is partially supported by The Research Council of Norway as a part of the Engineering Predictability with Embodied Cognition (EPEC) project, under grant agreement 240862  ... 
doi:10.1109/ssci.2016.7850237 dblp:conf/ssci/MiseikisGET16 fatcat:ksoe7oth4jcjdhf6jrgb4z2xri

Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks [article]

Philipp Kratzer, Marc Toussaint, Jim Mainprice
2020 arXiv   pre-print
In order to alleviate this issue, we propose a prediction framework that decouples short-term prediction, linked to internal body dynamics, and long-term prediction, linked to the environment and task  ...  In this work we investigate encoding short-term dynamics in a recurrent neural network, while we account for environmental constraints, such as obstacle avoidance, using gradient-based trajectory optimization  ...  The authors thank the International Max Planck Research School for Intelligent Systems (IMPRS-IS) for supporting Philipp Kratzer.  ... 
arXiv:1910.01843v2 fatcat:ugb5sqsa2nbhxc7c4j7bsle6oi

CHOMP: Covariant Hamiltonian optimization for motion planning

Matt Zucker, Nathan Ratliff, Anca D. Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher M. Dellin, J. Andrew Bagnell, Siddhartha S. Srinivasa
2013 The international journal of robotics research  
In this paper, we present CHOMP (covariant Hamiltonian optimization for motion planning), a method for trajectory optimization invariant to reparametrization.  ...  CHOMP uses functional gradient techniques to iteratively improve the quality of an initial trajectory, optimizing a functional that trades off between a smoothness and an obstacle avoidance component.  ...  Acknowledgments We thank Gil Jones and Willow Garage for their support, particularly in performing ROS experiments.  ... 
doi:10.1177/0278364913488805 fatcat:lelp5mb6xrbwpli6npvpotli74

Differentially constrained mobile robot motion planning in state lattices

Mihail Pivtoraiko, Ross A. Knepper, Alonzo Kelly
2009 Journal of Field Robotics  
We compute a set of elementary motions that connects each discrete state value to a set of its reachable neighbors via feasible motions. Thus, this set of motions induces a connected search graph.  ...  We ensure that all paths in the graph encode feasible motions via the imposition of continuity constraints on state variables at graph vertices and compliance of the graph edges with a differential equation  ...  Control Sets with Shortest Edges Algorithm 1 is a simple inverse method for generating a control set, as introduced in Section 2.1.  ... 
doi:10.1002/rob.20285 fatcat:ro2rxetkpncnbgfwxqh3zez7ge

Human-aware motion reshaping using dynamical systems

Matteo Saveriano, Fabian Hirt, Dongheui Lee
2017 Pattern Recognition Letters  
In this work, we present a real-time approach for human-aware motion replanning using a two-level hierarchical architecture.  ...  in case of unforeseen obstacles (including the human), and iii) to replan online the current task taking into account the human behavior.  ...  Graduate School of Science and Engineering.  ... 
doi:10.1016/j.patrec.2017.04.014 fatcat:rmhry6ctz5d3vcexcjo4mn32me

High-DOF Robots in Dynamic Environments Using Incremental Trajectory Optimization

Chonhyon Park, Jia Pan, Dinesh Manocha
2014 International Journal of Humanoid Robotics  
We present a novel optimization-based motion planning algorithm for high degree-offreedom (DOF) robots in dynamic environments.  ...  We compute collision-free and smooth paths using optimization-based planning and trajectory perturbation for each sub-problem.  ...  Acknowledgments This research is supported in part by ARO Contracts W911NF-10-1-0506 and NSF awards 1000579, 1117127, 1305286.  ... 
doi:10.1142/s0219843614410011 fatcat:fi2jtbnnljeojfhdqbbokhl2xi
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