Zachary Bell's repositories
two_link_control
Nonlinear adaptive controller for a two-link arm
odom_estimator
Estimate velocity from mocap pose
Deep-Reinforcement-Learning-Hands-On
Hands-on Deep Reinforcement Learning, published by Packt
gazebo_states_odom
Subscribes to the gazebo states topic and publishes an odom
linear_adp
adp for linear systems
single_agent_herding_n_agents_nn
Estimate the interaction dynamics between cooperative and uncooperative agents and herd uncooperative agents to a desired location
adp_staf_pp_dynamic
Approximate the optimal policy to move through dynamic avoidance regions
aleph_star
Reinforcement learning with A* and a deep heuristic
DeepMRAC
This code implements Deep Model Reference Adaptive Controller for a WingRock System
differentiable-particle-filters
Source code and data for the paper "Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors"
ext_cam_calibrate
extrinsic calibration for monocular camera
feedback_denied_switched_path_following
Switched systems approach to following a path in feedback denied region by entering a feedback region before uncertainty grows too large.
homog_track
vision project using homography
icl_stationary
Estimate the distance to features and the path of a monocular camera
opencv
Open Source Computer Vision Library
pyGAT
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
RL-Adventure-2
PyTorch0.4 implementation of: actor critic / proximal policy optimization / acer / ddpg / twin dueling ddpg / soft actor critic / generative adversarial imitation learning / hindsight experience replay
scalable_agent
A TensorFlow implementation of Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
single_agent_herding_adp
Estimate the interaction dynamics between a cooperative and uncooperative agent and approximate the optimal policy to herd the uncooperative agent to the desired location
smac
SMAC: The StarCraft Multi-Agent Challenge
streetlearn
A C++/Python implementation of the StreetLearn environment based on images from Street View, as well as a TensorFlow implementation of goal-driven navigation agents solving the task published in “Learning to Navigate in Cities Without a Map”, NeurIPS 2018