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Multi-agent Collaborative Perception for Autonomous Driving: Unsettled Aspects
- Research Report
- EPR2023017
Sector:
Language:
- English
Topic:
Affiliated:
This report delves into the field of multi-agent collaborative perception (MCP)
for autonomous driving: an area that remains unresolved. Current single-agent
perception systems suffer from limitations, such as occlusion and sparse sensor
observation at a far distance.
Multi-agent Collaborative Perception for Autonomous Driving: Unsettled
Aspects addresses three unsettled topics that demand immediate
attention:
- Establishing normative communication protocols to facilitate seamless information sharing among vehicles
- Defining collaboration strategies, including identifying specific collaboration projects, partners, and content, as well as establishing the integration mechanism
- Collecting sufficient data for MCP model training, including capturing diverse modal data and labeling various downstream tasks as accurately as possible