Obstacle Avoidance Using Deep Q Learning

May 25, 2026
Quick Context: A goal-driven autonomous mapping and exploration system that combines reactive and planned robot navigation. Nikolaj Witting, Fidel Esquivel Estay, Johannes Lienhart, and Paula Wulkop from ETH Zurich implement dynamic

Obstacle Avoidance Using Deep Q Learning -

A goal-driven autonomous mapping and exploration system that combines reactive and planned robot navigation. Nikolaj Witting, Fidel Esquivel Estay, Johannes Lienhart, and Paula Wulkop from ETH Zurich implement dynamic

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  • A goal-driven autonomous mapping and exploration system that combines reactive and planned robot navigation.
  • Nikolaj Witting, Fidel Esquivel Estay, Johannes Lienhart, and Paula Wulkop from ETH Zurich implement dynamic

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Obstacle Avoidance using Deep Q learning

Obstacle Avoidance using Deep Q learning

Read more details and related context about Obstacle Avoidance using Deep Q learning.

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Obstacle Avoidance using Reinforcement Learning

Read more details and related context about Obstacle Avoidance using Reinforcement Learning.

Dynamics Obstacle Avoidance using Deep Reinforcement Learning

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Deep Reinforcement Learning-based Obstacle Avoidance in Continuous Navigation

Deep Reinforcement Learning-based Obstacle Avoidance in Continuous Navigation

A goal-driven autonomous mapping and exploration system that combines reactive and planned robot navigation. First ...

Wall following and obstacle avoidance using Q-Learning (Reinforcement Learning)

Wall following and obstacle avoidance using Q-Learning (Reinforcement Learning)

Read more details and related context about Wall following and obstacle avoidance using Q-Learning (Reinforcement Learning).

Obstacle Avoidance using Q learning

Obstacle Avoidance using Q learning

Read more details and related context about Obstacle Avoidance using Q learning.

Reinforcement Learning for obstacle avoidance

Reinforcement Learning for obstacle avoidance

Read more details and related context about Reinforcement Learning for obstacle avoidance.

Implementing vision based dynamic obstacle avoidance in Duckietown

Implementing vision based dynamic obstacle avoidance in Duckietown

Nikolaj Witting, Fidel Esquivel Estay, Johannes Lienhart, and Paula Wulkop from ETH Zurich implement dynamic

Deep Reinforcement Learning Obstacle Avoidance

Deep Reinforcement Learning Obstacle Avoidance

Read more details and related context about Deep Reinforcement Learning Obstacle Avoidance.

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Decentralized Multi-agent Collision Avoidance with Deep Reinforcement Learning

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