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https://github.com/singhaman1750/Legged-Robots

This repository contains papers in the field of legged robots.
https://github.com/singhaman1750/Legged-Robots

Last synced: 2 months ago
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This repository contains papers in the field of legged robots.

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README 

        
# Legged-Robots: Introduction

This repository contains papers, videos and other references in the field of legged robots. 



# Robotics conference paper lists

1. **List of all ICRA 2024 paper:** [[Webpage](https://ras.papercept.net/conferences/conferences/ICRA24/program/ICRA24_ContentListWeb_3.html#thal-ex_07)]

2. **List of all IROS 2023 papers:** [[Google sheet](https://docs.google.com/spreadsheets/d/1cdca2J4g2gmHym1J0nXxJabhsxK7xIfXxicB8Le6AwU/edit#gid=214014586)] / [[Github Repo](https://github.com/ryanbgriffiths/IROS2023PaperList)]

3. **List of all ICRA 2023 papers:** [[Google sheet](https://docs.google.com/spreadsheets/d/1LcYjqrh8EyZ4HIeSl80ECF-rb7tND6DTdUj2p5XA2gM/edit?usp=sharing)]



# :page_with_curl: Papers



## :robot: ICRA 2023

### Learning for locomotion

1. DribbleBot: Dynamic Legged Manipulation in the wild [[Paper](https://arxiv.org/pdf/2304.01159.pdf)][[Video](https://www.youtube.com/watch?v=1cek5Ypa3TE)][[Code](https://github.com/Improbable-AI/dribblebot)][[Notes](https://github.com/singhaman1750/Research-Paper-Notes/blob/main/README.md#dribblebot-dynamic-legged-manipulation-in-the-wild)]

3. Learning Low-Frequency Motion Control for Robust and Dynamic Robot Locomotion [[Paper](https://arxiv.org/pdf/2209.14887.pdf)][[Video](https://www.youtube.com/watch?v=pSuX223zLvM)][[Website](https://ori-drs.github.io/lfmc/)]

4. OPT-Mimic: Imitation of Optimized Trajectories for Dynamic Quadruped Behaviors [[Paper](https://arxiv.org/pdf/2210.01247.pdf)][[Video](https://www.youtube.com/watch?v=tDzu_sy_FAI)][[Website](https://www.cs.ubc.ca/~van/papers/2022-opt-mimic/index.html)]

5. Learning to Walk by Steering: Perceptive Quadrupedal Locomotion in Dynamic Environments [[Paper](https://arxiv.org/pdf/2209.09233.pdf)][[Video](https://www.youtube.com/watch?v=_BvLqx3wAxI)][[Website](https://ut-austin-rpl.github.io/PRELUDE/)][[Code](https://github.com/UT-Austin-RPL/PRELUDE)]

6. Legs As Manipulator: Pushing Quadrupedal Agility Beyond Locomotion [[Paper](https://robot-skills.github.io/resources/legmanip.pdf)][[Video](https://www.youtube.com/watch?v=d3YCmkEC7V0)][[Website](https://robot-skills.github.io/)]

8. Advanced Skills through Multiple Adversarial Motion Priors in Reinforcement Learning [[Paper](https://arxiv.org/pdf/2203.14912.pdf)][[Video](https://www.youtube.com/watch?v=kEdr0ARq48A)]

9. Deep Reinforcement Learning Based Personalized Locomotion Planning for Lower-Limb Exoskeletons [[Paper](https://drive.google.com/file/d/14PA0VKAiWc2FTyhFR9K-gvJtley7bxu4/view?usp=sharing)][[Video](https://www.youtube.com/watch?v=4K6bbGmHXzM)]

10. Expanding Versatility of Agile Locomotion through Policy Transitions Using Latent State Representation [[Paper](https://drive.google.com/file/d/1EuNl98amlAcvD2tDjjzNumYR6FHRXFVt/view?usp=sharing)][[Video](https://www.youtube.com/watch?v=bESzX20Akpg)]

11. Sim-To-Real Transfer for Quadrupedal Locomotion Via Terrain Transformer [[Paper](https://arxiv.org/pdf/2212.07740.pdf)]

12. Agile and Versatile Robot Locomotion Via Kernel-Based Residual Learning [[Paper](https://arxiv.org/pdf/2302.07343.pdf)][[Video](https://www.youtube.com/watch?v=bUZJadWCRXU)]



--------



## :joystick: Legged Robot Control:

### Optimization Based control for legged robots:

1. **Survey Paper**: Optimization-Based Control for Dynamic Legged Robots [[Paper](https://arxiv.org/abs/2211.11644)]

2. **Convex MPC for Quadruped walking**: Dynamic Locomotion in the MIT Cheetah 3 Through Convex Model-Predictive Control [[Paper](https://ieeexplore.ieee.org/document/8594448)]

3. **Feedback MPC**: Feedback MPC for Torque-Controlled Legged Robots [[Paper](https://arxiv.org/abs/1905.06144)]

4. **RF-MPC**: Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds [[Paper](https://arxiv.org/abs/2012.10002)] [[Github](https://github.com/YanranDing/RF-MPC)]

5. **Motion Imitation**: Learning Agile Robotic Locomotion Skills by Imitating Animals [[Paper](https://arxiv.org/abs/2004.00784)] [[Github](https://github.com/erwincoumans/motion_imitation)]

6. **Non-Linear RF-MPC**: Real-Time Constrained Nonlinear Model Predictive Control on SO(3) or Dynamic Legged Locomotion [[Paper](http://ras.papercept.net/images/temp/IROS/files/2325.pdf)]

7. **WBC+MPC**: Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control [[Paper](https://arxiv.org/abs/1909.06586)]



### Quadruped Learning Based locomotion:

1. **RMA**: RMA: Rapid Motor Adaptation for Legged Robots [[Paper](https://www.roboticsproceedings.org/rss17/p011.pdf)]

2. **Walk These Ways**: Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior [[Paper](https://arxiv.org/abs/2212.03238)]

3. **DreamWaQ**: DreamWaQ: Learning Robust Quadrupedal Locomotion with Implicit Terrain Imagination Via Deep Reinforcement Learning [[Paper](https://arxiv.org/pdf/2301.10602.pdf)][[Video](https://www.youtube.com/watch?v=J5wl0be5KQM)][[Website](https://sites.google.com/view/dreamwaq)]

4. **HIMloco**: Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response [[Paper](https://arxiv.org/abs/2312.11460)]

5. **Tencent Robotics**: Lifelike Agility and Play on Quadrupedal Robots using Reinforcement Learning and Deep Pre-trained Models [[Paper](https://tencent-roboticsx.github.io/lifelike-agility-and-play/)][[Website](https://tencent-roboticsx.github.io/lifelike-agility-and-play/)][[Video](https://www.youtube.com/watch?v=ucucrLqT5dM)]

6. **Linear Policy**: Force Control for Robust Quadruped Locomotion: A Linear Policy Approach [[Paper](https://ieeexplore.ieee.org/document/10161080)][[Video](https://www.youtube.com/watch?v=k89QdImcqdo&t=2s)][[Website](https://www.stochlab.com/projects/LinPolForceControlQuad.html)]

7. **PIP-Loco**: Pip-Loco: A propioceptive Infinite Horizon Planning Framework for Quadrupedal Robot Locomotion [[Paper](https://arxiv.org/pdf/2409.09441)]



### Application of Learning-based locomotion on Quadrupeds:

1.  **DribbleBot**: DribbleBot: Dynamic Legged Manipulation in the wild [[Paper](https://arxiv.org/pdf/2304.01159.pdf)][[Video](https://www.youtube.com/watch?v=1cek5Ypa3TE)][[Code](https://github.com/Improbable-AI/dribblebot)][[Notes](https://github.com/singhaman1750/Research-Paper-Notes/blob/main/README.md#dribblebot-dynamic-legged-manipulation-in-the-wild)]

2. Legs As Manipulator: Pushing Quadrupedal Agility Beyond Locomotion [[Paper](https://robot-skills.github.io/resources/legmanip.pdf)][[Video](https://www.youtube.com/watch?v=d3YCmkEC7V0)][[Website](https://robot-skills.github.io/)]



### Humanoids Learning based locomotion:

1. Bi-Level Motion Imitation for Humanoid Robots [[Paper](https://openreview.net/forum?id=wH7Wv0nAm8)]

--------



## :hammer_and_wrench:	Legged Robot Mechanical Design

### :page_facing_up: Design Principles for legged robots:

1. **MIT, Design Principles**: Design principles for highly efficient quadrupeds and implementation on the MIT Cheetah robot [[Paper](https://ieeexplore.ieee.org/document/6631038)]



### :dog: Quadruped Robot Design Papers:

1. **MIT Cheetah-3**: MIT Cheetah 3: Design and Control of a Robust, Dynamic Quadruped Robot [[Paper](https://ieeexplore.ieee.org/document/8593885)]

2. **MIT Mini Cheetah**: Mini Cheetah: A Platform for Pushing the Limits of Dynamic Quadruped Control [[Paper](https://ieeexplore.ieee.org/document/8793865)] [[Blog](https://build-its.blogspot.com/2019/12/the-mini-cheetah-robot.html)]

3. **MIT Super Mini-Cheetah**: The MIT Super Mini Cheetah: A small, low-cost quadrupedal robot for dynamic locomotion [[Paper](https://ieeexplore.ieee.org/document/7443018)]

4. **ANYmal Robot**: ANYmal - A Highly Mobile and Dynamic Quadrupedal Robot [[Paper](https://ieeexplore.ieee.org/document/7758092)]

5. **KAIST, HOUND design**: Design of KAIST HOUND, a Quadruped Robot Platform for Fast and Efficient Locomotion with Mixed-Integer Nonlinear Optimization of a Gear Train [[Paper](https://ieeexplore.ieee.org/abstract/document/9811755)]

6. **Barry Robot**: Barry: A High-Payload and Agile Quadruped Robot [[Paper](https://ieeexplore.ieee.org/document/10246325)]

7. **UIUC, Panther**: Design and experimental implementation of a quasi-direct-drive leg for optimized jumping [[Paper](https://ieeexplore.ieee.org/document/8202172)]

8. **Stanford Doggo**: Stanford Doggo, an open source quasi-direct drive quadruped [[Paper](https://github.com/Nate711/StanfordDoggoProject)] [[Github](https://github.com/Nate711/StanfordDoggoProject)]

9. **Solo Robot**: An Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research [[Paper](https://ieeexplore.ieee.org/document/9015985)]

10. **MiniTaur**: Design Principles for a Family of Direct-Drive Legged Robots [[Paper](https://ieeexplore.ieee.org/document/7403902)]

11. **Stoch, IISc**: Design, Development and Experimental Realization of A Quadrupedal Research Platform: Stoch [[Paper](https://ieeexplore.ieee.org/document/8813480)]

12. **Tachyon, Sony**: Tachyon: Design and Control of High Payload, Robust, and Dynamic Quadruped Robot with Series-Parallel Elastic Actuators [[Paper](https://ieeexplore.ieee.org/document/9636196)]

13. **Raibo Robot, KAIST**: RaiBo: A versatile robo-dog that runs through a sandy beach at 3 meters per second [[News-Article](https://techxplore.com/news/2023-01-raibo-versatile-robo-dog-sandy-beach.html)] [[Video](https://www.youtube.com/watch?v=ATvFSwkneu4)]



### :robot: Humanoid Robot Design:

1. **Berkely Humanoid**: Berkeley Humanoid: A Research Platform for Learning-based Control [[Paper](https://arxiv.org/abs/2407.21781)]

2. **MIT Humanoid**: Design and Development of the MIT Humanoid: A Dynamic and Robust Research Platform [[Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10375199)]

3. **UIUC, Tello Leg**: Tello Leg: The Study of Design Principles and Metrics for Dynamic Humanoid Robots [[Paper](https://ieeexplore.ieee.org/document/9813569)]

4. **UIUC, Tello Leg**: The dynamic effect of mechanical losses of transmissions on the equation of motion of legged robots [[Paper](https://arxiv.org/abs/2106.01842)]

5. **AMI, IIT, Italy, egroCub Humanoid**: Optimization of Humanoid Robot Designs for Human-Robot Ergonomic Payload Lifting [[Paper](https://arxiv.org/abs/2211.13503)]

6. **Tiktok, Humanoid, Cornell University**: [[Website](http://ruina.tam.cornell.edu/research/topics/locomotion_and_robotics/Tik-Tok/)] 



### :joystick: :hammer_and_wrench: Co-Design Optimization:

1. Vitruvio: An Open-Source Leg Design Optimization Toolbox for Walking Robots [[Paper](https://ieeexplore.ieee.org/document/9157985)]

2. **Co-design(CACTO)**: Exploring the Limits of a Redundant Actuation System Through Co-Design [[Paper](https://ieeexplore.ieee.org/document/9400808)]

3. Meta Reinforcement Learning for Optimal Design of Legged Robots [[Paper](https://arxiv.org/pdf/2210.02750.pdf)]



### :electron: Electric motor based Actuator Designs for Legged Robots:

1. **KAIST, Actuator Design**: DRPD, Dual Reduction Ratio Planetary Drive for Articulated Robot Actuators [[Paper](https://ieeexplore.ieee.org/abstract/document/9981201)]

2. **Dual Motor Design (2021)**: Explosive Electric Actuator and Control for Legged Robots [[Paper](https://reader.elsevier.com/reader/sd/pii/S2095809921005282?token=528592F31700C12282D3918FF7D6AC7D58F2B05BE168CEA0767BE07971464D4F37986B7E089D0A53D6F9E87E12E5AB73&originRegion=eu-west-1&originCreation=20230413064751)]

3. **John Harry Bell, Master's Thesis, MIT (2018)**: A Two-Motor Actuator for Legged Robotics Applications [[Thesis](https://dspace.mit.edu/bitstream/handle/1721.1/127152/1191839946-MIT.pdf?sequence=1&isAllowed=y)]

4. **Robotics and Multibody Mechanics Research Group (R&MM), Belgium (2017)**: Modeling and design of an energy-efficient dual-motor actuation unit with a

planetary differential and holding brakes [[Paper](https://reader.elsevier.com/reader/sd/pii/S0957415817301812?token=FAB5BDB0EADAEA7F8CA91AD6F2AB31755882038340745DCBB9D1AB5AA3D244E6B66C7BE60CC0D6E7334D1A3368EB0343&originRegion=eu-west-1&originCreation=20230413064458)]

5. **Alexandre Girard's paper, Hamburg, Germany IROS(2015)**: A Two-Speed Actuator for Robotics with Fast Seamless Gear Shifting [[Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7354047)]

6. **Hoyul Lee's Paper, ASME/IEEE Transactions on mechatronics(2012)**: A New Actuator System Using Dual-Motors and a Planetary Gear [[Paper](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6022796)]

7. **Jung Jun Park' paper, ASME/IEEE Transactions on mechatronics(2010)**: A Serial-Type Dual Actuator Unit With Planetary Gear Train: Basic Design and Applications [[Paper](https://dspace.mit.edu/bitstream/handle/1721.1/127152/1191839946-MIT.pdf?sequence=1&isAllowed=y)]



-------------------------



# Patents

1. **Boston Dynamics**: [List of Patents from Boston Dynamics](https://www.bostondynamics.com/patents)

2. **Boston Dynamics**: [Screw Actuator for Legged Robots](https://patents.google.com/patent/US10253855B2/en)

3. **Boston Dynamics**: [WO2018112097 - TRANSMISSION WITH INTEGRATED OVERLOAD PROTECTION FOR A LEGGED ROBOT](https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2018112097)



-------



# Robotics Workshops Websites and video links

1. **ICRA 2024 Workshop on Co-design in Robotics: Theory, Practice, and Challenges**: [[Webpage](https://www.robotmechanisms.org/activities/icra-2024-codesign)]

2. **ICRA 2024 Advancements in Trajectory Optimization and Model Predictive Control for Legged Systems**: [[Webpage](https://atompc-workshop.github.io/)]



--------------



# Video Lectures: 

## Robotics and Controls:

1. Robotics Fall 2023, by Pranav Bhounsule: [[Videos](https://youtube.com/playlist?list=PLc7bpbeTIk77plTksRXAe1JPJZVmBNk8_&feature=shared)][[Notes](https://pab47.github.io/robotics/robotics23.html)]



## Topics in Mathematics 

1. [MIT 18.06 Linear Algebra, Spring 2005, MITOCW: Gilbert Strang](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)



## Optimization

1. **Course:** [Numerical Optimization, *(NPTEL)*: Shirish Sevade ](https://www.youtube.com/playlist?list=PLEAYkSg4uSQ3Hi2kc4n4bqJvxrtyaQa3P)



**Trajectory Optimization** 

1. **Video Lecture:** [Introduction to Trajectory Optimization: Matthew Kelly](https://www.youtube.com/watch?v=wlkRYMVUZTs)

3. **Video Lecture:** [Underactuated Robotics, Trajectory Optimization I: Lec 11, *Russ Tedrake*](https://www.youtube.com/watch?v=fY6gAo88Aa0)

4. **Video Lecture:** [Underactuated Robotics, Trajectory Optimization II: Lec 12, *Russ Tedrake*](https://www.youtube.com/watch?v=Mo9fTJmWAJY)

5. **Video Lecture:** [Optimization, Optimal Control, Trajectory Optimization, and Splines: Jesus Tordesillas](https://www.youtube.com/watch?v=j82Ia436DYY)

6. **Book:** Practical Methods for Optimal control and estimation using non-linear programming, John T. Betts

7. **Github Repos:** [Matthew Kelly's TrajOpt Repo](https://github.com/MatthewPeterKelly/OptimTraj)

8. **Github Repos:** [MindtPy Library Page: MINLP solver](https://pyomo.readthedocs.io/en/stable/contributed_packages/mindtpy.html)

9. **Tutorial Paper:** [An Introduction to Trajectory Optimization: How to do your own direct collocation, *Matthew Kelly*](https://www.matthewpeterkelly.com/research/MatthewKelly_IntroTrajectoryOptimization_SIAM_Review_2017.pdf)



## Basics of Control systems

1. Linear Quadratic Regulator (LQR): [Basics/Overview](https://www.youtube.com/watch?v=1_UobILf3cc) [Derivation]()



## Reinforcement Learning

1. [Deep RL Bootcamp](https://sites.google.com/view/deep-rl-bootcamp/lectures)

2. [Reinforcement Learning: David Silver](https://www.youtube.com/playlist?list=PLzuuYNsE1EZAXYR4FJ75jcJseBmo4KQ9-)

3. [CS-285: Deep Reinforcement Learning, UC Berkeley](http://rail.eecs.berkeley.edu/deeprlcourse/)

4. [Spinning up*](https://spinningup.openai.com/en/latest/index.html): It's a blog but really useful



## ROS

1. [ROS Wiki Tutorials: Muhammad Luqman](https://www.youtube.com/playlist?list=PLBbhfIdh4NdgBBkX7q0Y3UukO2_ZoICee)



## Mechanical Design and Theory

1. [Kinematics of Mechanisms and Machines: NPTEL, IIT KGP](https://www.youtube.com/playlist?list=PLbRMhDVUMngdCkMipemSKP_dCgZLLfOe8)

      1. [Lec-37: Gear Kinematics](https://www.youtube.com/watch?v=BjkxYZ93Fbs&list=PLbRMhDVUMngdCkMipemSKP_dCgZLLfOe8&index=38) 

      2. [Lec-38: Gear Trains I](https://www.youtube.com/watch?v=lu_Qw4Y4XRQ&list=PLbRMhDVUMngdCkMipemSKP_dCgZLLfOe8&index=39)

      3. [Lec-39: Gear Trains II](https://www.youtube.com/watch?v=5f3wBlRY8dQ&list=PLbRMhDVUMngdCkMipemSKP_dCgZLLfOe8&index=40)

      4. [Lec-40: Gear Trains III](https://www.youtube.com/watch?v=-aHRWEXB3h4&list=PLbRMhDVUMngdCkMipemSKP_dCgZLLfOe8&index=41)

2. [Bond Graph Modeling: NPTEL](https://www.youtube.com/watch?v=M8Nam032vgE)

3. [Gear Strength Theory: NPTEL](https://archive.nptel.ac.in/courses/112/106/112106137/)

4. [Friction-Model-for-Spur-Gear-transmission-efficiency: Review by Tsuneji Yada](https://www.jstage.jst.go.jp/article/jsmec1993/40/1/40_1_1/_article)



## Miscellaneous:

1. [List-of-Science-and-Math-courses](https://github.com/Developer-Y/math-science-video-lectures)



-------

# Usefull Books:



1. [Statics and Dynamics: Andy Ruina](http://ruina.tam.cornell.edu/Book/RuinaPratap-July-12-2019.pdf)



-------

# Useful Tools:



## Mathematics:

1. **Lean**: Programming Language for Theorem prover [[Link](https://lean-lang.org/)] \

      i. **Tutorials**: Natural Number Game [[Link](https://adam.math.hhu.de/#/g/leanprover-community/nng4)]



-------



# Useful articles:



## Software installations:

1. [Installing Anaconda on Ubuntu 22.04](https://linuxhint.com/install-anaconda-ubuntu-22-04/)

2. [Installing Anaconda on Ubuntu 18.04](https://www.digitalocean.com/community/tutorials/how-to-install-anaconda-on-ubuntu-18-04-quickstart)



## Technical topics:

1. [DDP](http://www.imgeorgiev.com/2023-02-01-ddp/): A good read for DDP

2. [Policy Gradient Algorithms](https://lilianweng.github.io/posts/2018-04-08-policy-gradient/#what-is-policy-gradient): A good read for Policy Gradient Algos

3. [Reinforcement Learning Resources](https://stable-baselines.readthedocs.io/en/master/guide/rl.html): A list of resources for studying Reinforcement Learning

4. [What are Diffusion Models?](https://lilianweng.github.io/posts/2021-07-11-diffusion-models/)



## Study:

1. **How to read Research Papers?**

      * How to read a research paper by *Andrew NG*: [Video](https://www.youtube.com/watch?v=733m6qBH-jI) / [Notes](https://github.com/IvLabs/ResearchPaperNotes/tree/master/literature_study_tips)

      * How to Read a Paper by *S. Keshav*: [PDF](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf)

      * How to read a paper: [LinkedIn Post](https://www.linkedin.com/feed/update/urn:li:activity:7044621048364900352?utm_source=share&utm_medium=member_desktop)

      * Usefull Resources by *Ness B Shroff*, on PhD and writing papers: [Webpage](https://newslab.ece.ohio-state.edu/for%20students/index.html)

2. **How to organize Reasearch Papers?**

      * How to find, read and organize papers by *Maya Gosztyla*: [Article](https://www.nature.com/articles/d41586-022-01878-7)



## Know your scientist:

1. [Steven LaValle](http://lavalle.pl/bio.html): Motivating story of Steven LaValle, who gave the RRT algorithm.

2. [Shuji Nakamura: Invention of Blue LED](https://youtu.be/AF8d72mA41M?feature=shared): Documentary about invention of blue LED.



## Website:

1. [List of usefull resources: Aditya Mehrotra, MIT D-lab](https://www.adim.io/resources)

2. [StePhane Caron](https://scaron.info/category/robotics.html)

3. [Usefull Resources: Xiaobin Xiong](https://www.xiaobinxiong.info/resources)



## Productivity Articles: (Don't get sucked too much into them)

1. [HBR: 5 Mental Mistakes That Kill Your Productivity by Alice Boyes](https://hbr.org/2019/11/5-mental-mistakes-that-kill-your-productivity?utm_medium=social&utm_campaign=hbr&utm_source=facebook&tpcc=orgsocial_edit)



## Cool AI tools:

1. [InstantID](https://huggingface.co/spaces/InstantX/InstantID) : Merges your picture with text description and an optional pose photo

2. [Perplexity.ai](https://perplexity.ai/) : A replacement for ChatGPT. It is real-time and it continuously searches the internet.

3. [Text to Image Playground](https://huggingface.co/spaces/MisterProton/text-to-image-models-playground): COnvert text to image with free credits addition.



----------------------



# Useful GitHub Repositories:



1. [loco-3d/crocoddyl:](https://github.com/loco-3d/crocoddyl)

Crocoddyl is an optimal control library for robot control under contact sequence. Its solver is based on various efficient Differential Dynamic Programming (DDP)-like algorithms



2. [Pinocchio:](https://github.com/stack-of-tasks/pinocchio?tab=readme-ov-file#examples)

   Efficient and Versatile Rigid Body Dynamics Algorithms



---------------------

# List of Robotics Conferences and Journals:

1. **List of Top Robotics Conferences and Publications**: [[List on Google Scholar Webpage](https://scholar.google.com/citations?view_op=top_venues&hl=en&vq=eng_robotics)]

      1. *A few ASME Conferences and Journals*:

            1. Journal of Mechanisms and Robots,

            2. Journal of Dynamics Systems, Measurement and Control, and

            3. Transaction on Mechatronics (IEEE/ASME) etc

      2. *A few IEEE Conferences and Journals*:

            1. International Conference on Robotics and Automation (ICRA),

            2. International Conference on Intelligent Robots and Systems (IROS),

            3. Robotics and Automation Letters (RAL),

            4. Transaction on Robotics (T-RO) etc.

        

2. **IEEE publication recommender:** [[Link](https://publication-recommender.ieee.org/home)]



----------------------

---------------



# Professors and Labs working in legged robotics

## India

* **Shishir N Y**, Stochastic Robotics Lab, RBCCPS, IISc Bengaluru [[Personal Website](https://www.shishirny.com/)][[Lab website](https://www.stochlab.com/)]

* **Mangal Kothari**, IIT Kanpur: [[Homepage](https://home.iitk.ac.in/~mangal/)]



## USA

* **Sangbae Kim**, Biomimetics Robotics Lab, MIT [[Lab Website](https://biomimetics.mit.edu/)]

* **Pulkit Agarwal**, Improbable AI Lab, MIT [[Personal Website](https://people.csail.mit.edu/pulkitag/)]

* **Deepak Pathak**, CMU [[Personal Website](https://www.cs.cmu.edu/~dpathak/)]

* **Zac Manchester**, Robotic Exploration Group, CMU [[Personal Webpage](https://www.ri.cmu.edu/ri-faculty/zachary-manchester/)][[Lab Website](https://roboticexplorationlab.org/)]

* **Ye Zhao**, LIDAR lab, Georgia Tech [[Personal Website](https://sites.google.com/site/yezhaout)][[Lab Website](https://lab-idar.gatech.edu/)]

* **Sehoon Ha**, Georgia Tech [[Personal Website](https://faculty.cc.gatech.edu/~sha9/)]

* **Quan Nguyen**, Dynamic Robotics and Control Laboratory, University of South California (USC) [[Personal Webpage](https://viterbi.usc.edu/directory/faculty/Nguyen/Quan)][[Lab Website](https://sites.usc.edu/quann/)]

* **Pranav Bhounsule**, Robotics and Motion Laboratory, University of Illinois Chicago [[Personal Webpage](https://mie.uic.edu/profiles/bhounsule-pranav/)][[Lab Website](https://pab47.github.io/)]

* **Joao Ramos**, Robo Design Lab, University of Illinois Urbana-Champaign (UIUC) [[Lab Website](https://publish.illinois.edu/robodesign/)]

* **Ayonga Hereid**, Cyber-Physical and Robotics Lab, Ohio State University [[Personal Webpage](https://mae.osu.edu/people/hereid.1)][[Lab Webpage](https://mae.osu.edu/cyberbotics)]

* **Koushil Sreenath**, Hybrid Robotics, University of South California, Berkeley (USC, Berkeley) [[Personal Webpage](https://me.berkeley.edu/people/koushil-sreenath/)][[Lab Website](https://hybrid-robotics.berkeley.edu/)]

* **Jitendra Malik**, EECS, University of California at Berkeley [[Personal Webpage](https://homepages.laas.fr/ostasse/hugo/)]

* **Yanran Ding**, Robotics Department, University of Michigan [[Personal Website](https://sites.google.com/view/yanranding/home)]

* **Xiaobin Xiong**, UW WELL Lab, University of Wisconsin-Madison [[Personal Website](https://www.xiaobinxiong.info/about)][[Lab Website](https://well.robotics.wisc.edu/team/)]



## Europe

* **Marco Hutter**, Robotic Systems Lab, ETH Zurich, Switzerland [[Lab Website](https://rsl.ethz.ch/)]

* **Serena Ivaldi**, Research Scientist, INRIA, France [[Personal Website](https://members.loria.fr/SIvaldi/)]

* **Oliver Strasse**, French National Centre for Scientific Research, France [[Personal Website](https://homepages.laas.fr/ostasse/hugo/)]

* **Carlos Mastalli**, Heriot-Watt University, Edinburgh, UK [[Personal Website](https://cmastalli.github.io/)]



## South Korea

* **Hae-Won Park**, DRDC Lab, KAIST [[Lab Website](https://www.dynamicrobot.kaist.ac.kr/)]

* **Jemin Hwangbo**, RaiLab, KAIST [[Lab Website](https://www.railab.kaist.ac.kr/)]



## Other Labs

* **Sony Quadruped Research** [Website](https://www.sony.com/en/SonyInfo/research/technologies/new_mobility/)



---------------

# Robotics Companies

## India

* **Ideaforge**, Drone manufacturing company [[Website](https://ideaforgetech.com/)]

* **Ati Motors**, Industrial Mobile robots company [[Website](https://atimotors.com/)] 

---------------

# Accesories for Legged robots:



1. **Motors**

      1. [**TQ-Motors**](https://www.tq-group.com/de/produkte/tq-robodrive/): Used in Raibo Quadruped

      2. [**Halodi Motors**](https://futurerobotix.com/?product=revo1-30): Used in Hound quadruped

2. **Drivers**

      1. **Mjbots**: [Moteus-n1](https://mjbots.com/products/moteus-n1), [Moteus-r4.xx](https://mjbots.com/products/moteus-n1) \

                        It also provide several other accesories for legged robots. It is like a one stop shop.