Method and System for Robot Navigation in Unknown Environments
AssigneeCambridge Enterprise Limited
InventorsAmanda Prorok, Zhe Liu, Jan Blumenkamp, Binyu Wang
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Abstract
Broadly speaking, embodiments of the present techniques provide methods and systems for robot navigation in an unknown environment. In particular, the present techniques provide a navigation system comprising a navigating device and a sensor network comprising a plurality of static sensors. The sensor network is trained to predict a direction to a target object, and the navigating device is trained to reach the target object as efficiently as possible using information obtained from the sensor network.
Claims21
1-20. (canceled)
A computer-implemented method of training a machine learning, ML, model for a navigation system comprising a navigating device and a sensor network comprising a plurality of static sensors that are communicatively coupled together, the method comprising:
- training neural network modules of a first sub-model of the ML model to predict, using data captured by the plurality of static sensors, a direction corresponding to a shortest path to a target object, wherein the target object is detectable by at least one static sensor;
- and
- training neural network modules of a second sub-model of the ML model to guide, using information received from the plurality of static sensors, the navigating device to the target object.
A non-transitory machine readable media having instructions stored thereon, the instructions configured to cause a processor to train a machine learning, ML, model for a navigation system comprising a navigating device and a sensor network comprising a plurality of static sensors that are communicatively coupled together, by:
- training neural network modules of a first sub-model of the ML model to predict, using data captured by the plurality of static sensors, a direction corresponding to a shortest path to a target object, wherein the target object is detectable by at least one static sensor;
- and
- training neural network modules of a second sub-model of the ML model to guide, using information received from the plurality of static sensors, the navigating device to the target object.
A navigation system comprising:
- a sensor network comprising a plurality of static sensors, wherein each static sensor comprises a processor, coupled to memory, arranged to use a trained first sub-model of a machine learning, ML, model to:
- predict a direction corresponding to a shortest path to a target object, wherein the target object is detectable by at least one static sensor;
- and
- a navigating device comprising a processor, coupled to memory, arranged to use a trained second sub-model of the machine learning, ML, model to:
- guide the navigating device to the target object using information received from the plurality of static sensors.
Dependencies are inferred from the claim text.