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Robots and self-driving vehicles face a number of challenges when navigating through real environments. Successful navigation in dynamic environments requires prioritizing subtasks and monitoring resources. Animals are under similar constraints. It has been shown that the neuromodulator serotonin regulates impulsiveness and patience in animals. In the present paper, we take inspiration from the serotonergic system and apply it to the task of robot navigation. In a set of outdoor experiments, we show how changing the level of patience can affect the amount of time the robot will spend searching for a desired location. To navigate GPS compromised environments, we introduce a deep reinforcement learning paradigm in which the robot learns to follow sidewalks. This may further regulate a tradeoff between a smooth long route and a rough shorter route. Using patience as a parameter may be beneficial for autonomous systems under time pressure.
Navigation using only one marker, which contains four artificial features, is a challenging task since camera pose estimation using only four coplanar points suffers from the rotational ambiguity problem in a real-world application. This paper presen
In autonomous driving, navigation through unsignaled intersections with many traffic participants moving around is a challenging task. To provide a solution to this problem, we propose a novel branched network G-CIL for the navigation policy learning
We present a navigation system that combines ideas from hierarchical planning and machine learning. The system uses a traditional global planner to compute optimal paths towards a goal, and a deep local trajectory planner and velocity controller to c
In this paper, we present the Role Playing Learning (RPL) scheme for a mobile robot to navigate socially with its human companion in populated environments. Neural networks (NN) are constructed to parameterize a stochastic policy that directly maps s
Odometer has been proven to significantly improve the accuracy of the Global Navigation Satellite System / Inertial Navigation System (GNSS/INS) integrated vehicle navigation in GNSS-challenged environments. However, the odometer is inaccessible in m