18 citations · 52 across the 8 of their papers we have counts for
6 papers · 1 filter
A Sample-Based Approach for Hierarchical Information-Theoretic Compression of Probabilistic Occupancy Grids
Zhenyu Jin, Daniel T. Larsson
We develop a sample-based framework for constructing information-driven hierarchical multi-resolution representations of probabilistic occupancy grids. Recent methods compute infor…
Communication-aware Hierarchical Map Compression of Time-Varying Environments for Mobile Robots
Daniel T. Larsson, Dipankar Maity
In this paper, we develop a systematic framework for the time-sequential compression of dynamic probabilistic occupancy grids. Our approach leverages ideas from signal compression…
Information-theoretic Abstraction of Semantic Octree Models for Integrated Perception and Planning
Daniel T. Larsson, Arash Asgharivaskasi, Jaein Lim +2
In this paper, we develop an approach that enables autonomous robots to build and compress semantic environment representations from point-cloud data. Our approach builds a three-d…
Information-Theoretic Abstractions for Resource-Constrained Agents via Mixed-Integer Linear Programming
Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras
In this paper, a mixed-integer linear programming formulation for the problem of obtaining task-relevant, multi-resolution, graph abstractions for resource-constrained agents is pr…
Information-Theoretic Abstractions for Planning in Agents with Computational Constraints
Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras
In this paper, we develop a framework for path-planning on abstractions that are not provided to the agent a priori but instead emerge as a function of the available computational…
Q-Search Trees: An Information-Theoretic Approach Towards Hierarchical Abstractions for Agents with Computational Limitations
Daniel T. Larsson, Dipankar Maity, Panagiotis Tsiotras
In this paper, we develop a framework to obtain graph abstractions for decision-making by an agent where the abstractions emerge as a function of the agent's limited computational…