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Apoorva Vashisth

3 accepted papers

2026

Scalable Multi-Robot Informative Path Planning for Target Mapping via Deep Reinforcement Learning

RA-L 2026

Autonomous robots are widely utilized for mapping and exploration tasks due to their cost-effectiveness. Multi-robot systems offer scalability and efficiency, especially in terms of the number of robots deployed in more complex environments. These tasks belong to the set of Multi-Robot Informative P

Cited by 1SourcecodeScholar
2024

Deep Reinforcement Learning With Dynamic Graphs for Adaptive Informative Path Planning

RA-L 2024

Autonomousrobots are often employed for data collection due to their efficiency and low labour costs. A key task in robotic data acquisition is planning paths through an initially unknown environment to collect observations given platform-specific resource constraints, such as limited battery life.

Cited by 39SourcecodeScholar
2022

CAtNIPP: Context-Aware Attention-based Network for Informative Path Planning

CoRL 2022poster

Informative path planning (IPP) is an NP-hard problem, which aims at planning a path allowing an agent to build an accurate belief about a quantity of interest throughout a given search domain, within constraints on resource budget (e.g., path length for robots with limited battery life). IPP requir…

Cited by 32SourceScholar