Harshal Maske

According to our database1, Harshal Maske authored at least 13 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Stochastic Deep Koopman Model for Quality Propagation Analysis in Multistage Manufacturing Systems.
CoRR, 2023

2021
Task Learning, Intent Prediction, and Adaptive Blended Shared Control With Application to Excavators.
IEEE Trans. Control. Syst. Technol., 2021

2019
Large-scale traffic control using autonomous vehicles and decentralized deep reinforcement learning.
Proceedings of the 2019 IEEE Intelligent Transportation Systems Conference, 2019

2018
Blended Shared Control with Subgoal Adjustment.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Learning Task-Based Instructional Policy for Excavator-Like Robots.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Likelihood Rate Based Estimation of Nonstationary Markov Models.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Methods for Blended Shared Control of Hydraulic Excavators with Learning and Prediction.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

Sensor Selection via Observability Analysis in Feature Space.
Proceedings of the 2018 Annual American Control Conference, 2018

2017
Teaching and Learning using Semantic Labels.
Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, 2017

2016
Can Co-robots Learn to Teach?
CoRR, 2016

Kernel Observers: Systems-Theoretic Modeling and Inference of Spatiotemporally Evolving Processes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Intent aware shared control in off-nominal situations.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
Kernel controllers: A systems-theoretic approach for data-driven modeling and control of spatiotemporally evolving processes.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015


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