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STORM: An Integrated Framework for Fast Joint-Space Model-Predictive Control for Reactive Manipulation
[article]
2021
arXiv
pre-print
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In this paper, we develop a system for fast, joint space sampling-based MPC for manipulators that is efficiently parallelized using GPUs. ...
Sampling-based model-predictive control (MPC) is a promising tool for feedback control of robots with complex, non-smooth dynamics, and cost functions. ...
However, manipulation tasks often involve Our sampling-based model-predictive control framework operates in the joint space to enable a robot to achieve manipulation objectives such as tracking a moving ...
arXiv:2104.13542v2
fatcat:3tfrs3eh3nex7fwicravdvr62a
SE3-Pose-Nets: Structured Deep Dynamics Models for Visuomotor Planning and Control
[article]
2017
arXiv
pre-print
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We further show that our model can be used for closed-loop control directly in the learned low-dimensional pose space, where the actions are computed by minimizing error in the pose space using gradient-based ...
Our deep dynamics model, a variant of SE3-Nets, learns a low-dimensional pose embedding for visuomotor control via an encoder-decoder structure. ...
We would also like to thank NVIDIA for generously providing a DGX used for this research via the UW NVIDIA AI Lab (NVAIL). ...
arXiv:1710.00489v1
fatcat:gvacvwuexzdbvlwuxw2ywsec6e
Hierarchical planning architectures for mobile manipulation tasks in indoor environments
2010
2010 IEEE International Conference on Robotics and Automation
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This paper describes a hierarchical planner deployed on a mobile manipulation system. ...
We place a premium on fast response, so the global planner achieves speed by using a very rough approximation of the robot kinematics, and the local planner begins execution of the next action even without ...
Local Planner The arm controller relies on a combination of model predictive and PID control. ...
doi:10.1109/robot.2010.5509669
dblp:conf/icra/KnepperSM10
fatcat:j7cxkhpbjnfvxn2ahu4vot6y4i
Compensation of Nonlinear Torsion in Flexible Joint Robots: Comparison of Two Approaches
2016
IEEE transactions on industrial electronics (1982. Print)
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2015 pre-print arXiv:1507.07067v1 fatcat:vn4zmajxp5b5lmzcksy3gh652aOther Versions
The second approach relies on the modeling of motor drives and inverse hysteresis and uses the generalized momenta when predicting the joint torsion. ...
In this paper, two approaches for compensating the nonlinear joint torsion with hysteresis are described and compared with each other. ...
The observed reactive joint torque allows for computing the relative joint torsion. Thus, the motor drive feedback control operates in the 'virtual' joint link space by accounting for torsion. ...
doi:10.1109/tie.2016.2574299
fatcat:mdokjsrt3zatnlx3kzu55pqhby
Real-time Perception meets Reactive Motion Generation
[article]
2017
arXiv
pre-print
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This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. ...
only reacts to local environment dynamics and (iii) a reactive planner that integrates feedback control and motion optimization. ...
On real robotic platforms, kinematic models and measured joint angles are commonly inaccurate and therefore lead to erroneous predictions of end-effector pose relative to the camera. ...
arXiv:1703.03512v3
fatcat:y3y25efvw5fsjeqw6j3xh7glve
Flexible-Joint Manipulator Trajectory Tracking with Learned Two-Stage Model employing One-Step Future Prediction
[article]
2021
arXiv
pre-print
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Flexible-joint manipulators are frequently used for increased safety during human-robot collaboration and shared workspace tasks. ...
We compare joint position, joint velocity and end-effector position tracking accuracy against the classical baseline controller and several simpler models. ...
INTRODUCTION Robot manipulators have been used for decades, and trajectory tracking control has been extensively researched to achieve fast and accurate motion. ...
arXiv:2112.02979v1
fatcat:ity4vwokzrb2vipd45wilz3h6a
Efficient and Reactive Planning for High Speed Robot Air Hockey
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2107.06140v1 fatcat:chogdbmecjbe3k3cln5hd6ykbq
Using two Kuka Iiwa 14, we show how to design a policy for general-purpose robotic manipulators for the air hockey game. ...
For these reasons, this environment is perfect for pushing to the limit the performance of currently available general-purpose robotic manipulators. ...
After each prediction step, we apply the collision model from [1] . Every time a collision happens, we don't update the covariance matrix, as it is hard to model the bounce uncertainty. ...
arXiv:2107.06140v2
fatcat:dj2k2ybwabchzlrgana6c4e6ne
Motion Control of a Robot Manipulator in Free Space Based on Model Predictive Control
[chapter]
2008
Robot Manipulators
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As shown in the previous section, the joint space velocity can be predicted using eq. (7). ...
Application to manipulators This part aims at showing how Model Predictive Control can be efficiently applied to robot manipulators to suit their fast servo rate. ...
Motion Control of a Robot Manipulator in Free Space Based on Model Predictive Control, Robot Manipulators, Marco Ceccarelli (Ed.), ISBN: 978-953-7619-06-0, InTech, Available from: http://www.intechopen.com ...
doi:10.5772/6202
fatcat:hdc2wlitnjg37lcy3fejasf6ea
A hierarchical approach to minimum-time control of industrial robots
2016
2016 IEEE International Conference on Robotics and Automation (ICRA)
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Model predictive control is used in order to achieve reactive system behavior and to obtain accurate local approximations of the collision avoidance constraints (which are nonconvex). ...
Our formulation is applied to the online generation of trajectories for industrial robots performing pick and place operations in the presence of obstacles. ...
We achieve a reactive behavior by using model predictive control, and our approach has the capacity to suppress high frequency chattering in the control signal in the presence of noise: a common drawback ...
doi:10.1109/icra.2016.7487386
dblp:conf/icra/HomsiSDW16
fatcat:hkd2d5rrk5e7xfmfwq3kz3meti
Plan-Based Control of Joint Human-Robot Activities
2010
Künstliche Intelligenz
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We present a newly emerging application for autonomous robots: companion robots that are not merely machines performing tasks for humans, but assistants that achieve joint goals with humans. ...
This collaborative aspect entails specific challenges for AI and robotics. ...
Joint intention theory [4] provides a basis for modeling the commitment of the cooperation partners to a joint tasks. ...
doi:10.1007/s13218-010-0043-1
fatcat:xqiez7dgm5hfplr7ucksh5snye
A Proactive Strategy for Safe Human-Robot Collaboration based on a Simplified Risk Analysis
2015
Modeling, Identification and Control
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Kinematic redundancy was exploited for simultaneous task performance within task constraints, and risk minimization. Sphere-based geometric models were used both for the human and robot. ...
Based on this risk field, a control algorithm that constantly reduces the current risk within its task constraints was developed. ...
Implementing this or similar strategies could also provide a predictive model, based on the likelihood analysis. ...
doi:10.4173/mic.2015.1.2
fatcat:hp7ldvtrkrcpphpnkg4ebpzj6y
Prediction-based reactive control strategy for human-robot interactions
2010
2010 IEEE International Conference on Robotics and Automation
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In this paper a reactive control strategy intended for human-robot interactions (HRI) is presented. A conventional reactive control scheme is reviewed first. ...
This is followed by the introduction of a new prediction-based reactive control strategy. ...
Prediction-Based Reactive Control Strategy In this section, a new prediction-based reactive control strategy for human-safe robots is proposed. ...
doi:10.1109/robot.2010.5509179
dblp:conf/icra/NajmaeiK10
fatcat:gixmpchwkbhbtdr6gkaajvs76q
Collaborative Behavior Models for Optimized Human-Robot Teamwork
[article]
2020
arXiv
pre-print
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In this work, we describe a novel Model Predictive Control (MPC)-based framework for finding optimal trajectories in a collaborative, multi-agent setting, in which we simultaneously plan for the robot ...
We use human-robot handovers to demonstrate that with a strong model of the collaborator, our framework produces fluid, reactive human-robot interactions in novel, cluttered environments. ...
We derive predictive models for each external, i.e., uncontrolled, agent and an optimal control objective for the controlled agent, i.e.the robot. ...
arXiv:1910.04339v2
fatcat:gg4qlehnwfc2nd2btsbzr5dtzu
Comparing Alternate Modes of Teleoperation for Constrained Tasks
[article]
2019
arXiv
pre-print
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Our experiments show that higher performance is achieved when humans submit commands in low-dimensional task spaces as opposed to joint space manipulations. ...
, task-informed control space while having the robot optimize for achieving desired job properties. ...
typically model manipulation tasks in the task space. ...
arXiv:1905.04428v1
fatcat:simzxlpe35b4ja7wvuuhvxabfe
Multi 3D camera mapping for predictive and reflexive robot manipulator trajectory estimation
2016
2016 IEEE Symposium Series on Computational Intelligence (SSCI)
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2016 pre-print arXiv:1610.03646v1 fatcat:hspdd3gnlzhpjimdxomz3cms5m
However, robot control can be still a limiting factor for better adaptation of these technologies. ...
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
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