Three-Dimensional Path-Following Control of a Robotic Airship with Reinforcement Learning
نویسندگان
چکیده
منابع مشابه
Backward and forward path following control of a wheeled robot
A wheeled mobile robot is one of the most important types of mobile robots. A subcategory of these robots is wheeled robots towing trailer(s). Motion control problem, especially in backward motion is one of the challenging research topics in this field. In this article, a control algorithm for path-following problem of a tractor-trailer system is provided, which at the same time provides the ab...
متن کاملA Platform for Autonomous Path Control of Unmanned Airship
But there is a set of aircraft tasks that takes long times, are monotonous, are performed in sensitive geographic places that demands specialized equipment and well trained crew. The examples of these tasks are: surveillance, patrol, data collection, search and rescue and so on. These tasks are being progressively substituted by drones or robotic aircrafts, which eliminated crew fatigue and imp...
متن کاملA Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical techniques from optimal control and dynamic programming with modern learning techniques from statistical estimation theory. In this vein, this paper suggests to use the framework of stochastic optimal control with path in...
متن کاملReinforcement Learning for Robotic Locomotions
● Modifications on constraints Since TRPO is a constraint optimization problem, our first thought is replacing the KL constraint by some other constraints that also measure policy similarity. A natural thought would be using MSE loss on . We noticed later that this in fact corresponds to the standard policy gradient update. We have also tried to directly optimize the objective without any const...
متن کاملAn Integrated Connectionist Approach to Reinforcement Learning for Robotic Control
We explore the use of a connectionist-learning system designed to allow the application of reinforcement learning to robot control. In particular, we compare direct and indexed partitioning methods and nd indexed partitioning has advantages in time and space complexity, learning speed (measured in trials), and success rate. We make these comparisons based on extensive simulations and runs on a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Aerospace Engineering
سال: 2019
ISSN: 1687-5966,1687-5974
DOI: 10.1155/2019/7854173