Information-theoretic approach to efficient adaptive path planning for mobile robotic environmental sensing

ICAPS 2009 - Proceedings of the 19th International Conference on Automated Planning and Scheduling

Volumn , Issue , 2009, Pages 233-240

  Low, Kian Hsiang ^a   Dolant, John M ^a,b   Khosla, Pradeep ^a,b  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE PATH PLANNING; ADAPTIVE POLICY; ADAPTIVITY; DECISION-THEORETIC; ENVIRONMENT MODELS; ENVIRONMENTAL SENSING; EXPLORATION POLICY; EXPLORATION TASKS; GAUSSIAN PROCESSES; HIGH RESOLUTION; HOT SPOT; INFORMATION-THEORETIC APPROACH; MAXIMUM ENTROPY SAMPLING; MOBILE ROBOTIC; PERFORMANCE QUALITY; PLANNING UNDER UNCERTAINTY; ROBOT EXPLORATION; ROBOT TEAMS; SUFFICIENT CONDITIONS; THEORETICAL BOUNDS; TIME COMPLEXITY;

GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); INFORMATION THEORY; MAPPING; OPTIMIZATION; ROBOTS; SCHEDULING;

ROBOT PROGRAMMING;

EID: 78650599306     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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