From 219909955e904ac82079aa8664d24887a11faf24 Mon Sep 17 00:00:00 2001 From: Simon Jones Date: Thu, 25 Apr 2024 22:01:34 -0400 Subject: [PATCH] doc: rephrasing goals to indicate past tense rather than future tense --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 3a79eaf..f1e46d7 100644 --- a/README.md +++ b/README.md @@ -37,13 +37,13 @@ Spring 2024 This project aims to train the COEX Clover quadcopter equipped with an array of Time of Flight (ToF) sensors to perform basic navigation and obstacle avoidance in randomized scenarios using a Deep Deterministic Policy Gradient (DDPG) -reinforcement learning algorithm. Using randomized environments will test the +reinforcement learning algorithm. Using randomized environments tests the effectiveness of curriculum learning for reinforcement learning and the overall strengths and weaknesses of DDPG for quadcopter control. By training the -quadcopter to explore randomized environments, this can also demonstrate how -using simpler, more economically affordable sensors can enable a quadcopter to -fly in a GPS-denied environment without the use of LiDAR, which is typically an -order of magnitude more expensive. +quadcopter to explore randomized environments, this also demonstrates how using +simpler, more economically affordable sensors could potentially enable a +quadcopter to fly in a GPS-denied environment without the use of LiDAR, which is +typically an order of magnitude more expensive. ## Quick Start