Deep Obstacle Avoidance∗
نویسنده
چکیده
We present work on a robot system capable of rapidly learning to avoid obstacles in previously unseen environments. We exploit deep learning’s generalized features to reason about when to turn left, turn right, or drive straight within an indoor environment. We present preliminary results of a deep convolutional neural network trained without any pre-training that can successfully avoid obstacles.
منابع مشابه
Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning
Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding collision becomes significantly more challenging due to the lack of 3D information. Conventional path planners for obstacle avoidance require tuning a number of parameters and do not have the ability to directly benefi...
متن کاملDynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملObstacle avoidance for an autonomous vehicle using force field method
This paper presents a force field concept for guiding a vehicle at a high speed maneuver. This method is similar to potential field method. In this paper, motion constrains like vehicles velocity, distance to obstacle and tire conditions and such lane change conditions as zero slop condition and zero lateral acceleration are discussed. After that, possible equations as vehicles path ar...
متن کاملLearning Robust Bed Making using Deep Imitation Learning with DART
Bed-making is a universal home task that can be challenging for senior citizens due to reaching motions. Automating bed-making has multiple technical challenges such as perception in an unstructured environments, deformable object manipulation, obstacle avoidance and sequential decision making. We explore how DART, an LfD algorithm for learning robust policies, can be applied to automating bed ...
متن کاملLow Cost Obstacle Avoidance Robot
52 Abstract— This paper deals with a low cost solution to obstacle avoidance for a mobile robot. This paper also presents a dynamic steering algorithm which ensures that the robot doesn't have to stop in front of an obstacle which allows robot to navigate smoothly in an unknown environment, avoiding collisions. The obstacle avoidance strategy has been described. Obstacle avoidance strategy and ...
متن کامل