Follow-Bench is a unified simulation benchmark for robot person following that re-implements eight planners and evaluates their safety-comfort trade-offs across varied target paths, crowds, and environments, with real-robot validation.
Rda: An accelerated collision free motion planner for autonomous navigation in cluttered environments,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
DPNet uses Doppler LiDAR with a Doppler Kalman neural network for obstacle tracking and Doppler-tuned MPC for real-time ego-motion planning to achieve high-frequency accurate navigation in highly dynamic environments.
citing papers explorer
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Follow-Bench: A Unified Motion Planning Benchmark for Socially-Aware Robot Person Following
Follow-Bench is a unified simulation benchmark for robot person following that re-implements eight planners and evaluates their safety-comfort trade-offs across varied target paths, crowds, and environments, with real-robot validation.
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DPNet: Doppler LiDAR Motion Planning for Highly-Dynamic Environments
DPNet uses Doppler LiDAR with a Doppler Kalman neural network for obstacle tracking and Doppler-tuned MPC for real-time ego-motion planning to achieve high-frequency accurate navigation in highly dynamic environments.