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ARMCHAIR: integrated inverse reinforcement learning and model predictive control for human-robot collaboration

ARMCHAIR: integrated inverse reinforcement learning and model predictive control for human-robot collaboration

Angelo Caregnato-Neto
Luciano Cavalcante Siebert
Arkady Zgonnikov
Marcos Ricardo Omena de Albuquerque Máximo
R. J. Afonso
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Papers citing "ARMCHAIR: integrated inverse reinforcement learning and model predictive control for human-robot collaboration"

9 / 9 papers shown
Title
Using Models Based on Cognitive Theory to Predict Human Behavior in Traffic: A Case Study
Using Models Based on Cognitive Theory to Predict Human Behavior in Traffic: A Case Study
J. Schumann
Aravinda Ramakrishnan Srinivasan
Jens Kober
Gustav Markkula
Arkady Zgonnikov
109
8
0
24 May 2023
Robust Robot Planning for Human-Robot Collaboration
Robust Robot Planning for Human-Robot Collaboration
Yang You
Vincent Thomas
F. Colas
Rachid Alami
Olivier Buffet
37
4
0
27 Feb 2023
Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming
Real-time motion planning and decision-making for a group of differential drive robots under connectivity constraints using robust MPC and mixed-integer programming
Angelo Caregnato-Neto
Marcos R. O. A. Máximo
R. J. Afonso
38
9
0
31 May 2022
Core Challenges of Social Robot Navigation: A Survey
Core Challenges of Social Robot Navigation: A Survey
Christoforos Mavrogiannis
Francesca Baldini
Allan Wang
Dapeng Zhao
Pete Trautman
Aaron Steinfeld
Jean Oh
60
247
0
09 Mar 2021
Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments
Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments
Hai Zhu
Francisco Martínez Claramunt
B. Brito
Javier Alonso-Mora
54
51
0
10 Feb 2021
Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments
Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments
Alessandro Sestini
A. Kuhnle
Andrew D. Bagdanov
36
7
0
04 Dec 2020
Multi-Agent Adversarial Inverse Reinforcement Learning
Multi-Agent Adversarial Inverse Reinforcement Learning
Lantao Yu
Jiaming Song
Stefano Ermon
75
135
0
30 Jul 2019
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
Rohin Shah
Noah Gundotra
Pieter Abbeel
Anca Dragan
49
72
0
23 Jun 2019
Learning Robust Rewards with Adversarial Inverse Reinforcement Learning
Learning Robust Rewards with Adversarial Inverse Reinforcement Learning
Justin Fu
Katie Z Luo
Sergey Levine
129
757
0
30 Oct 2017

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