3 accepted papers
We propose combining preference and rating query types into a mixed-type query selection to learn reward functions for robotic decision making to improve scientific data collection. Mixed-type query selection allows the scientist operating a robot to specify the robot’s tradeoffs and goals in terms …
We propose combining preference and rating query types into a mixed-type query selection to learn reward functions for robotic decision making to improve scientific data collection. Mixed-type query selection allows the scientist operating a robot to specify the robot's tradeoffs and goals in terms
This paper presents a framework that uses language instructions to define the constraints and objectives for robots gathering information about their environment. Designing autonomous robotic sampling missions requires deep knowledge of both autonomy systems and scientific domain expertise. Language…