A Constrained-Optimization Approach to the Execution of Prioritized Stacks of Learned Multi-Robot Tasks
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Abstract (arXiv)
This paper presents a constrained-optimization formulation for the prioritized execution of learned robot tasks. The framework lends itself to the execution of tasks encoded by value functions, such as tasks learned using the reinforcement learning paradigm. The tasks are encoded as constraints of a convex optimization program by using control Lyapunov functions. Moreover, an additional constraint is enforced in order to specify relative priorities between the tasks. The proposed approach is showcased in simulation using a team of mobile robots executing coordinated multi-robot tasks.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 20 of its 36 references that are in the map. First posted on arXiv 13 Jan 2023.
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20 of 36 references.
References · 20
- 2021Convex optimizationcited by 2,479
- 2017A Survey on Multi-Task Learningcited by 838
- 2018Multi-Task Learning as Multi-Objective Optimizationcited by 809
- 2017An Overview of Multi-Task Learning in Deep Neural Networkscited by 791
- 2017Federated Multi-Task Learningcited by 669
- 2017Reinforcement Learning with Deep Energy-Based Policiescited by 659
- 2018Data-Efficient Hierarchical Reinforcement Learningcited by 436
- 2019Challenges of Real-World Reinforcement Learningcited by 282
- 2017Distral: Robust Multitask Reinforcement Learningcited by 231
- 2019MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policiescited by 105
- 2021Reset-Free Reinforcement Learning via Multi-Task Learning: Learning Dexterous Manipulation Behaviors without Human Interventioncited by 90
- 2018Composable Deep Reinforcement Learning for Robotic Manipulationcited by 70
8 more
- 2017Divide-and-Conquer Reinforcement Learningcited by 46
- 2018Riemannian Motion Policiescited by 45
- 2019Composing Task-Agnostic Policies with Deep Reinforcement Learningcited by 20
- 2017Learning to Compose Skillscited by 15
- 2019An Optimal Task Allocation Strategy for Heterogeneous Multi-Robot Systemscited by 6
- 2019Riemannian Motion Policy Fusion through Learnable Lyapunov Function Reshapingcited by 6
- 2021Composable Geometric Motion Policies using Multi-Task Pullback Bundle Dynamical Systemscited by 4
- 2020A Set-Theoretic Approach to Multi-Task Execution and Prioritizationcited by 2
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