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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.  ...  Finally, we predict reaching motions from the human's current configuration to a task-space goal region by iteratively re-planning a trajectory using the learned cost function.  ...  We use goal set trajectory optimization in both IOC and Iterative Re-Planning.  ... 
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.  ...  Finally, we predict a human's motion for a given task by iteratively re-planning a trajectory for a 23 DoFs human kinematic model using the STOMP algorithm with the learned cost function in the presence  ...  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

Human-Like Arm Motion Generation: A Review

Gianpaolo Gulletta, Wolfram Erlhagen, Estela Bicho
2020 Robotics  
In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning.  ...  For these reasons, human-like arm motion generation may not fully respect human behavioral and neurological key features and may result restricted to specific tasks of human-robot interaction.  ...  For instance, Park and Kim [91] described an optimal database construction of human re-targeted motion to learn arm motion primitives for a real-time human-like trajectory planning.  ... 
doi:10.3390/robotics9040102 fatcat:fahjlaf6hraslknxo7ifw5o4au

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

Intention-Aware Motion Planning Using Learning Based Human Motion Prediction

Jae Sung Park, Chonhyon Park, Dinesh Manocha
2017 Robotics: Science and Systems XIII  
We present a motion planning algorithm to compute collision-free and smooth trajectories for high-DOF robots interacting with humans in a shared workspace.  ...  We represent the predicted human motion using a Gaussian distribution and compute tight upper bounds on collision probabilities for safe motion planning.  ...  RELATED WORKS In this section, we give a brief overview of prior work on human motion prediction, task planning for human-robot collaborations, and motion planning in environments shared with humans.  ... 
doi:10.15607/rss.2017.xiii.045 dblp:conf/rss/ParkPM17 fatcat:a3pgv2hi3zecfj4x4nwnrrkerq

Goal-Directed Reasoning and Cooperation in Robots in Shared Workspaces: an Internal Simulation Based Neural Framework

Ajaz A. Bhat, Vishwanathan Mohan
2018 Cognitive Computation  
In the setting of an industrial task where two robots are jointly assembling objects in a shared workspace, we describe a bioinspired neural architecture for goal-directed action planning based on coupled  ...  From social dining in households to product assembly in manufacturing lines, goal-directed reasoning and cooperation with other agents in shared workspaces is a ubiquitous aspect of our day-to-day activities  ...  need to be re-planned to avoid collisions.  ... 
doi:10.1007/s12559-018-9553-1 pmid:30147802 pmcid:PMC6096944 fatcat:mujplqwanjckphikysejs3gggq

Viewing Robot Navigation in Human Environment as a Cooperative Activity [article]

Harmish Khambhaita, Rachid Alami
2017 arXiv   pre-print
To meet human comparable efficiency, a robot needs to predict the human trajectories and plan its own trajectory correspondingly in the same shared space.  ...  Humans concurrently aid and comply with each other while moving in a shared space.  ...  Acknowledgements This work is supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 688147 (MuMMER project).  ... 
arXiv:1708.01267v2 fatcat:7u6dwupq7fbk5d36ayixe33csq

Viewing Robot Navigation in Human Environment as a Cooperative Activity [chapter]

Harmish Khambhaita, Rachid Alami
2019 Distributed Autonomous Robotic Systems  
To meet human comparable efficiency, a robot needs to predict the human trajectories and plan its own trajectory correspondingly in the same shared space.  ...  Humans concurrently aid and comply with each other while moving in a shared space.  ...  Acknowledgements This work is supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 688147 (MuMMER project).  ... 
doi:10.1007/978-3-030-28619-4_25 fatcat:66jbortttna5fjncueioccb2qi

I-Planner: Intention-Aware Motion Planning Using Learning Based Human Motion Prediction [article]

Jae Sung Park and Chonhyon Park and Dinesh Manocha
2017 arXiv   pre-print
We present a motion planning algorithm to compute collision-free and smooth trajectories for high-DOF robots interacting with humans in a shared workspace.  ...  We represent the predicted human motion using a Gaussian distribution and compute tight upper bounds on collision probabilities for safe motion planning.  ...  RELATED WORK In this section, we give a brief overview of prior work on human motion prediction, task planning for human-robot collaborations, and motion planning in environments shared with humans.  ... 
arXiv:1608.04837v5 fatcat:64ygzlhu6fcrrjkqtlaf23xsju

Towards Assessing the Human Trajectory Planning Horizon

Daniel Carton, Verena Nitsch, Dominik Meinzer, Dirk Wollherr, Catalin Buiu
2016 PLoS ONE  
This work considers optimal control and model predictive control approaches for accurate trajectory prediction and proposes to integrate aspects of human behavior to improve their performance.  ...  By modeling humans as model predictive controllers, the influence of the planning horizon is investigated in simulations.  ...  Acknowledgments This work is supported in part within the ERC Advanced Grant SHRINE Agreement No. 267877 (www.shrine-project.eu) and in part by the Technische Universität München-Institute for Advanced  ... 
doi:10.1371/journal.pone.0167021 pmid:27936015 pmcid:PMC5147863 fatcat:ucwlwmcjaverpecufzhyrqpoja

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 can be used to locally optimize feasible trajectories, as well as to solve motion planning queries, converging to low-cost trajectories even when initialized with infeasible ones.  ...  Acknowledgments We thank Gil Jones and Willow Garage for their support, particularly in performing ROS experiments.  ... 
doi:10.1177/0278364913488805 fatcat:lelp5mb6xrbwpli6npvpotli74

Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game [article]

Nigora Gafur, Gajanan Kanagalingam, Martin Ruskowski
2022 arXiv   pre-print
In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance.  ...  A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance.  ...  The former indicates that our approach enables flexible, real-time capable motion control and trajectory planning of multiple robots operating in the same workspace.  ... 
arXiv:2103.00583v2 fatcat:ezxlmxa74ne3ndwrcx75sasnbu

A Hybrid Framework for Understanding and Predicting Human Reaching Motions

Ozgur S. Oguz, Zhehua Zhou, Dirk Wollherr
2018 Frontiers in Robotics and AI  
Robots collaborating naturally with a human partner in a confined workspace need to understand and predict human motions.  ...  In motor control, reaching motions are framed as an optimization problem. However, different optimality criteria predict disparate motion behavior.  ...  AUTHOR CONTRIBUTIONS OO formulated and initiated the research. ZZ finalized the research and conducted the experiments. OO, ZZ, and DW wrote the paper.  ... 
doi:10.3389/frobt.2018.00027 pmid:33500914 pmcid:PMC7806050 fatcat:ovlxyuwdebbkjc4bjgy6m7xr4a

Learning Coupled Dynamical Systems from human demonstration for robotic eye-arm-hand coordination

Luka Lukic, Jose Santos-Victor, Aude Billard
2012 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012)  
We recorded gaze, arm, hand, and trunk data from human subjects in reaching and grasping scenarios with/without obstacle in the workspace.  ...  When facing perturbations, the system can re-plan its actions almost instantly, without the need for an additional planning module.  ...  Our work exploits this biologically inspired notion of forward models in motor control, and uses a model of the dynamics of the reaching motion to predict collisions with objects in the workspace when  ... 
doi:10.1109/humanoids.2012.6651574 dblp:conf/humanoids/LukicSB12 fatcat:esbc2ucllnd7hpcoj52mlchtqq

Realtime Trajectory Smoothing with Neural Nets [article]

Shohei Fujii, Quang-Cuong Pham
2022 arXiv   pre-print
In Realtime Motion Planning, obstacles are detected in real time through a vision system, and new trajectories are planned with respect to the current positions of the obstacles, and immediately executed  ...  Existing realtime motion planners, however, lack the smoothing post-processing step -- which are crucial in sampling-based motion planning -- resulting in the planned trajectories being jerky, and therefore  ...  However, such a solution is inefficient and precludes true human-robot collaboration, where humans and robots are to share a common workspace.  ... 
arXiv:2111.02165v2 fatcat:2onwykpghfbwnf45vevbygpdm4
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