add maniquad paper

README.md

@@ -45,6 +45,8 @@
 <details>
 <summary><b>2024</b></summary>
 
+<img src="./assets/2024.png" width="100%" class="center"/>
+
 - [Accessorizing Quadrupedal Robots with Wearable Electronics](https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202300633)
 - [Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion](https://arxiv.org/abs/2401.17583)
 - [Deep Compliant Control for Legged Robots](TBD)
@@ -53,6 +55,7 @@
 - [Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning](https://arxiv.org/abs/2309.14246)
 - [Learning to walk in confined spaces using 3D representation](https://arxiv.org/abs/2403.00187)
 - [Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network](https://arxiv.org/abs/2402.00366)
+- [ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots](https://arxiv.org/abs/2310.10486)
 - [OptiState: State Estimation of Legged Robots using Gated Networks with Transformer-based Vision and Kalman Filtering](https://arxiv.org/abs/2401.16719)
 - [Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg](https://arxiv.org/abs/2402.10837)
 - [ProNav: Proprioceptive Traversability Estimation for Legged Robot Navigation in Outdoor Environments](https://arxiv.org/abs/2307.09754)

assets/word_cloud.py

@@ -14,86 +14,30 @@
     "that", "that's", "the", "their", "theirs", "them", "themselves", "then", "there", "there's", "these", "they", "they'd", "they'll",
     "they're", "they've", "this", "those", "through", "to", "too", "under", "until", "up", "very", "via", "was", "we", "we'd", "we'll", "we're",
     "we've", "were", "what", "what's", "when", "when's", "where", "where's", "which", "while", "who", "who's", "whom", "why", "why's",
-    "with", "would", "you", "you'd", "you'll", "you're", "you've", "your", "yours", "yourself", "yourselves"
+    "with", "would", "you", "you'd", "you'll", "you're", "you've", "your", "yours", "yourself", "yourselves", "using"
 ])
 
 # 1. Get the paper list from the user
 # papers_input = input("Please provide the list of papers:\n")
 papers_input = """
-- [Adaptive Locomotion Learning for Quadruped Robots by Combining DRL with a Cosine Oscillator Based Rhythm Controller](https://www.mdpi.com/2076-3417/13/19/11045)
-- [Adaptive walking control for quadruped robot by using oscillation patterns](https://www.nature.com/articles/s42256-022-00576-3)
-- [AMP in the wild: Learning robust, agile, natural legged locomotion skills](https://arxiv.org/abs/2304.10888)
-- [ARMP: Autoregressive Motion Planning for Quadruped Locomotion and Navigation in Complex Indoor Environments](https://arxiv.org/abs/2303.15900)
-- [ArtPlanner: Robust Legged Robot Navigation in the Field](https://arxiv.org/abs/2303.01420)
-- [ASC: Adaptive Skill Coordination for Robotic Mobile Manipulation](https://arxiv.org/abs/2304.00410)
-- [Autonomous Stair Ascending and Descending by Quadruped Wheelchairs](https://ieeexplore.ieee.org/abstract/document/10202377)
-- [Barkour: Benchmarking Animal-level Agility with Quadruped Robots](https://arxiv.org/abs/2305.14654)
-- [Barry: A High-Payload and Agile Quadruped Robot](https://ieeexplore.ieee.org/document/10246325)
-- [Combining model-predictive control and predictive reinforcement learning for stable quadrupedal robot locomotion](https://arxiv.org/abs/2307.07752)
-- [Curiosity-Driven Learning of Joint Locomotion and Manipulation Tasks](https://openreview.net/forum?id=QG_ERxtDAP-&referrer=%5Bthe%20profile%20of%20Marco%20Hutter%5D(%2Fprofile%3Fid%3D~Marco_Hutter1))
-- [DeepTransition: Viability Leads to the Emergence of Gait Transitions in Learning Anticipatory Quadrupedal Locomotion Skills](https://arxiv.org/abs/2306.07419)
-- [DOC: Differentiable Optimal Control for Retargeting Motions onto Legged Robots](https://la.disneyresearch.com/wp-content/uploads/DOC_paper.pdf)
-- [Dojo: A Differentiable Physics Engine for Robotics](https://arxiv.org/abs/2203.00806)
-- [DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning](https://arxiv.org/abs/2301.10602)
-- [DribbleBot: Dynamic Legged Manipulation in the Wild](https://gmargo11.github.io/dribblebot/rsc/dribblebot_paper.pdf)
-- [Drilling Task with a Quadruped Robot for Silage Face Measurements](https://www.researchgate.net/publication/370765569_Drilling_Task_with_a_Quadruped_Robot_for_Silage_Face_Measurements)
-- [Event Camera-based Visual Odometry for Dynamic Motion Tracking of a Legged Robot Using Adaptive Time Surface](https://arxiv.org/abs/2305.08962)
-- [Event-based Agile Object Catching with a Quadrupedal Robot](https://arxiv.org/abs/2303.17479)
-- [Extreme Parkour with Legged Robots](https://arxiv.org/abs/2309.14341)
-- [Fast Traversability Estimation for Wild Visual Navigation](https://arxiv.org/abs/2305.08510)
-- [From Data-Fitting to Discovery: Interpreting the Neural Dynamics of Motor Control through Reinforcement Learning](https://arxiv.org/abs/2305.11107)
-- [Geometric Mechanics of Contact-Switching Systems](https://arxiv.org/abs/2306.10276)
-- [Guardians as You Fall: Active Mode Transition for Safe Falling](https://arxiv.org/abs/2310.04828)
-- [Hierarchical Experience-informed Navigation for Multi-modal Quadrupedal Rebar Grid Traversal](https://arxiv.org/abs/2311.08354)
-- [Identifying important sensory feedback for learning locomotion skills](https://www.nature.com/articles/s42256-023-00701-w)
-- [Intelligent Control of Multilegged Robot Smooth Motion: A Review](https://ieeexplore.ieee.org/document/10216974)
-- [iPlanner: Imperative Path Planning](https://arxiv.org/abs/2302.11434)
-- [Language to Rewards for Robotic Skill Synthesis](https://arxiv.org/abs/2306.08647)
-- [Layered Control for Cooperative Locomotion of Two Quadrupedal Robots: Centralized and Distributed Approaches](https://ieeexplore.ieee.org/document/10281391)
-- [Learning a Single Policy for Diverse Behaviors on a Quadrupedal Robot using Scalable Motion Imitation](https://arxiv.org/abs/2303.15331)
-- [Learning and Adapting Agile Locomotion Skills by Transferring Experience](https://arxiv.org/abs/2304.09834)
-- [Learning Arm-Assisted Fall Damage Reduction and Recovery for Legged Mobile Manipulators](https://www.research-collection.ethz.ch/handle/20.500.11850/595246)
-- [Learning Complex Motor Skills for Legged Robot Fall Recovery](https://ieeexplore.ieee.org/document/10138662/)
-- [Learning Impulse-Reduced Gait for Quadruped Robot using CMA-ES](https://ieeexplore.ieee.org/abstract/document/10202519)
-- [Learning quadrupedal locomotion on deformable terrain](https://www.science.org/doi/full/10.1126/scirobotics.ade2256)
-- [Learning to Exploit Elastic Actuators for Quadruped Locomotion](https://arxiv.org/abs/2209.07171)
-- [Learning to Walk by Steering: Perceptive Quadrupedal Locomotion in Dynamic Environments](https://arxiv.org/abs/2209.09233)
-- [Legs as Manipulator: Pushing Quadrupedal Agility Beyond Locomotion](https://arxiv.org/abs/2303.11330)
-- [LSC: Language-guided Skill Coordination](https://languageguidedskillcoordination.github.io/)
-- [LSTP: Long Short-Term Motion Planning for Legged and Legged-Wheeled Systems](https://www.research-collection.ethz.ch/handle/20.500.11850/625515)
-- [Mastering Diverse Domains through World Models](https://arxiv.org/abs/2301.04104)
-- [Max: A Wheeled-Legged Quadruped Robot for Multimodal Agile Locomotion](https://ieeexplore.ieee.org/document/10375960)
-- [Multi-Contact Whole Body Force Control for Position-Controlled Robots](https://arxiv.org/abs/2312.16465)
-- [Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion](https://arxiv.org/abs/2308.12517)
-- [OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors](https://arxiv.org/abs/2210.01247)
-- [ORBIT: A Unified Simulation Framework for Interactive Robot Learning Environments](https://ieeexplore.ieee.org/abstract/document/10107764)
-- [Orthrus: A Dual-arm Quadrupedal Robot for Mobile Manipulation and Entertainment Applications](https://ieeexplore.ieee.org/document/10309339)
-- [PyPose: A Library for Robot Learning with Physics-based Optimization](https://arxiv.org/abs/2209.15428)
-- [Real-Time Collision-Free Motion Planning and Control for Mobile Manipulation with Quadrupeds](https://ieeexplore.ieee.org/abstract/document/10354901)
-- [Reinforcement Learning for Legged Robots: Motion Imitation from Model-Based Optimal Control](https://arxiv.org/abs/2305.10989)
-- [Reinforcement Learning from Multiple Sensors via Joint Representations](https://arxiv.org/abs/2302.05342)
-- [Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End](https://arxiv.org/abs/2310.03581)
-- [Responsive CPG-Based Locomotion Control for Quadruped Robots](https://link.springer.com/chapter/10.1007/978-981-99-8073-4_22)
-- [RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion](https://arxiv.org/abs/2305.17842)
-- [RoboHive: A Unified Framework for Robot Learning](https://arxiv.org/abs/2310.06828)
-- [Robot Parkour Learning](https://openreview.net/forum?id=uo937r5eTE)
-- [Robust Quadrupedal Locomotion via Risk-Averse Policy Learning](https://arxiv.org/abs/2308.09405)
-- [Robust Recovery Motion Control for Quadrupedal Robots via Learned Terrain Imagination](https://arxiv.org/abs/2306.12712)
-- [Roll-Drop: accounting for observation noise with a single parameter](https://arxiv.org/abs/2304.13150)
-- [SafeSteps: Learning Safer Footstep Planning Policies for Legged Robots via Model-Based Priors](https://arxiv.org/abs/2307.12664.pdf)
-- [SayTap: Language to Quadrupedal Locomotion](https://arxiv.org/abs/2306.07580)
-- [Scientific Exploration of Challenging Planetary Analog Environments with a Team of Legged Robots](https://arxiv.org/abs/2307.10079)
-- [Skill Graph for Real-world Quadrupedal Robot Reinforcement Learning](https://openreview.net/forum?id=vdm4WnG5u-M)
-- [Solving Challenging Control Problems via Learning-based Motion Planning and Imitation](https://ieeexplore.ieee.org/abstract/document/10202250)
-- [Taking the First Step Toward Autonomous Quadruped Robots: The Quadruped Robot Challenge at ICRA 2023 in London [Competitions]](https://doi.org/10.1109/MRA.2023.3293296)
-- [Towards Legged Locomotion on Steep Planetary Terrain](https://www.research-collection.ethz.ch/handle/20.500.11850/625001)
-- [Tuning Legged Locomotion Controllers via Safe Bayesian Optimization](https://arxiv.org/abs/2306.07092)
-- [Versatile Multi-Contact Planning and Control for Legged Loco-Manipulation](https://www.science.org/doi/10.1126/scirobotics.adg5014)
+- [ManyQuadrupeds: Learning a Single Locomotion Policy for Diverse Quadruped Robots](https://arxiv.org/abs/2310.10486)
+- [Accessorizing Quadrupedal Robots with Wearable Electronics](https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.202300633)
+- [Agile But Safe: Learning Collision-Free High-Speed Legged Locomotion](https://arxiv.org/abs/2401.17583)
+- [Deep Compliant Control for Legged Robots](TBD)
+- [DTC: Deep Tracking Control](https://www.science.org/doi/10.1126/scirobotics.adh5401)
+- [Learning Quadrupedal High-Speed Running on Uneven Terrain](https://www.mdpi.com/2313-7673/9/1/37)
+- [Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning](https://arxiv.org/abs/2309.14246)
+- [Learning to walk in confined spaces using 3D representation](https://arxiv.org/abs/2403.00187)
+- [Legged Robot State Estimation With Invariant Extended Kalman Filter Using Neural Measurement Network](https://arxiv.org/abs/2402.00366)
+- [OptiState: State Estimation of Legged Robots using Gated Networks with Transformer-based Vision and Kalman Filtering](https://arxiv.org/abs/2401.16719)
+- [Pedipulate: Enabling Manipulation Skills using a Quadruped Robot's Leg](https://arxiv.org/abs/2402.10837)
+- [ProNav: Proprioceptive Traversability Estimation for Legged Robot Navigation in Outdoor Environments](https://arxiv.org/abs/2307.09754)
+- [Reduced Model Predictive Control Toward Highly Dynamic Quadruped Locomotion](https://ieeexplore.ieee.org/document/10418132/)
 """
 
 # 2. Ask the user for the title of the picture
 # picture_title = input("Please provide the title for the picture (without the .png extension): ")
-picture_title = "2023"
+picture_title = "2024"
 
 # 3. Extract the words from the titles (excluding the links)
 titles = re.findall(r"\[(.*?)\]\(.*?\)", papers_input)