Active Robotic Sensing as Decision Making with Statistical Methods
نویسندگان
چکیده
Active robotic sensing is a large field aimed at providing robotic systems with tools and methods for decision making under uncertainty, e.g. in a changing environment and lack of sufficient information. Active sensing (AS) incorporates the following aspects: (i) where to position sensors, (ii) how to make decisions for next actions in order to extract maximum information from the sensor data, and minimize costs such as travel time and energy. We concentrate on the second aspect: “Where should the robot move at the next time step?” and present AS in a probabilistic decision theoretic framework. The AS problem is formulated as a constrained optimization, with a multiobjective criterion combining an information gain and a cost term with respect to the generated actions. Solutions for AS of autonomous mobile robots are given, illustrating the framework.
منابع مشابه
A Comparison of Decision Making Criteria and Optimization Methods for Active Robotic Sensing
This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i) where to position sensors, and (ii) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. ...
متن کاملCorrelation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.
Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. ...
متن کاملRanking Passive Seismic Control Systems by Their Effectiveness in Reducing Responses of High-Rise Buildings with Concrete Shear Walls Using Multiple-Criteria Decision Making
In recent decades, the dual systems of steel moment-resisting frames and RC shear walls have found extensive application as lateral load-resisting systems for high-rise structures in seismically active areas. This paper investigated the effectiveness of tuned mass damper (TMD), viscous damper, friction damper, and the lead-core rubber bearing in controlling the damage and seismic response of hi...
متن کاملActive Sensing for Robotics – A Survey
This work surveys the major methods for model-based active sensing in robotics. Active sensing in robotics incorporates the following aspects: (i) where to position sensors, and (ii) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. The emphasis here is on B...
متن کاملActive Sensing as Bayes-Optimal Sequential Decision Making
Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of active sensing. Here, we present a Bayes-optimal inference and control framework for active sensing, C-DAC (Context-Dependent Active Controller). Unlike previously proposed algorithms that opt...
متن کامل