This video belongs to the ongoing Ph.D. thesis of Andre Mueller.
The approach of object-related navigation tries to amend some of the weaknesses that accompany global, map-based navigation approaches. Instead of incorporating the entire environment in the form of a heavily abstracted environment map into the planning routines, classified objects are considered, whose relevance for the task at hand is determined. Relative spatial information, which is gained by exploiting the local sensor data of the robot is directly conveyed to the planning and control routines instead of transforming the information into a global representation. By training movement models per driving maneuver, such as "overtake" or "turn left'", robot movement generation and object movement prediction in relation to other objects is achieved. These models allow to form plans of the sort: "follow lane", "then turn left on next crossroad", ..., which simplifies the reasoning routines and allows plans to be directly conveyed to a human observer and vice versa. The video shows that trained maneuver models are able to steer the autonomous robot MuCAR-3, when a route description of the form: "follow lane, then turn left on crossroad, follow lane, then turn right on crossroad" is provided. …...more
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