59 research outputs found
Learning a Group-Aware Policy for Robot Navigation
Human-aware robot navigation promises a range of applications in which mobile
robots bring versatile assistance to people in common human environments. While
prior research has mostly focused on modeling pedestrians as independent,
intentional individuals, people move in groups; consequently, it is imperative
for mobile robots to respect human groups when navigating around people. This
paper explores learning group-aware navigation policies based on dynamic group
formation using deep reinforcement learning. Through simulation experiments, we
show that group-aware policies, compared to baseline policies that neglect
human groups, achieve greater robot navigation performance (e.g., fewer
collisions), minimize violation of social norms and discomfort, and reduce the
robot's movement impact on pedestrians. Our results contribute to the
development of social navigation and the integration of mobile robots into
human environments.Comment: 8 pages, 4 figure
Development and validation of a method for detection and quantification of ochratoxin A in green coffee using liquid chromatography coupled to mass spectrometry
Evaluierung des Hämatologieautomaten Sysmex SF-3000 unter besonderer Berücksichtigung pädiatrischer und onkologischer Aspekte - Evaluation of the Hematology Analyzer Sysmex SF-3000 with Special Regard to Pediatric and Oncologic Aspects
Leachate recirculation between alternating aged refuse bioreactors and its effect on refuse decomposition
Effect of rapid hydraulic shock loads on the performance of granular bed baffled reactor
Application of nanotechnology based-biosensors in analysis of wine compounds and control of wine quality and safety: A critical review
Cold preservation of the small intestine with the new Celsior-solution First experimental results
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