Abstract: Various examples are directed to systems and methods for directing a field-of-view of a first sensor positioned on an autonomous vehicle. In one example, at least one processor selects a goal location on at least one travel way in an environment of the autonomous vehicle. The selecting of the goal location is based at least in part on map data describing at least one travel way in an environment of the autonomous vehicle and pose data describing a position of the autonomous vehicle in the environment. The at least one processor determines a field-of-view position to direct the first sensor towards the goal location based at least in part on the sensor position data. The at least one processor sends a field-of-view command to the first sensor. The field-of-view command modifies the field-of-view of the first sensor based on the field-of-view position.

Abstract: Various examples are directed to systems and methods for directing a field-of-view of a first sensor positioned on an autonomous vehicle. In one example, at least one processor selects a goal location on at least one travel way in an environment of the autonomous vehicle. The selecting of the goal location is based at least in part on map data describing at least one travel way in an environment of the autonomous vehicle and pose data describing a position of the autonomous vehicle in the environment. The at least one processor determines a field-of-view position to direct the first sensor towards the goal location based at least in part on the sensor position data. The at least one processor sends a field-of-view command to the first sensor. The field-of-view command modifies the field-of-view of the first sensor based on the field-of-view position.

Abstract: Various examples are directed to systems and methods for directing a field-of-view of a first sensor positioned on an autonomous vehicle. In one example, at least one processor selects a goal location on at least one travel way in an environment of the autonomous vehicle. The selecting of the goal location is based at least in part on map data describing at least one travel way in an environment of the autonomous vehicle and pose data describing a position of the autonomous vehicle in the environment. The at least one processor determines a field-of-view position to direct the first sensor towards the goal location based at least in part on the sensor position data. The at least one processor sends a field-of-view command to the first sensor. The field-of-view command modifies the field-of-view of the first sensor based on the field-of-view position.

Abstract: Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile device 10 by collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.

Abstract: Simultaneous 2-D room shape reconstruction and self-localization is accomplished using no pre-established infrastructure. A mobile device with co-located microphone and loudspeaker is used to collect echoes reflected by the walls. The system uniquely recovers arbitrary 2-D convex room shape as well as the position of mobile device 10 by collecting and processing distances between three consecutive measurement points as well as acoustic echoes from the device. A practical algorithm for room shape reconstruction and self-localization in the presence of noise and higher order echoes is proposed. Experimental results are provided to demonstrate the effectiveness of the approach.