Stanford Doggo is an open source quadruped robot that jumps, flips, and trots! robotcadquadrupedlegged-roboticsstanford-doggoquasi-directdirect-drive UpdatedJul 8, 2024 chvmp/champ Star1.8k Code Issues Pull requests MIT Cheetah I Implementation ...
Reinforcement learning framework for legged robot. - GitHub - zitongbai/legged_rl: Reinforcement learning framework for legged robot.
regret 指预测者(forecaster)的累计损失与专家(expert)之间的差,其用于度量预测者在事后有多后悔没有跟随专家的指导。 2.16Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior 2022.12.6 https://github.com/Improbable-AI/walk-these-ways 2022.dec.6 Conference on Robot Learn...
OCS2腿式机器人模型Legged Robot的范例为四足机器人Anymal,每条分支典型哺乳类三自由度设计。 整体为两个源码包: ocs2_robotics_examples/ocs2_legged_robot :最优化问题构建 ocs2_robotics_examples/ocs2_legged_robot_ros:ROS的有关接口 最优化问题 参考文献:A Unified MPC Framework for Whole-Body Dynamic Loco...
腿顺序:https://github.com/chengxuxin/extreme-parkour/issues/1 在legged_robot.py,line 284 defreindex(self,vec):returnvec[:,[3,4,5,0,1,2,9,10,11,6,7,8]]defreindex_feet(self,vec):returnvec[:,[1,0,3,2]]# LF LH RF RH --> LH LF RH RF ...
foc-wheel-legged-robot 一个新型结构的双轮腿机器人 HelloGitHub 评分 0 人评分 过去6 天共收获 2 颗 Star ✨ 开源•GPL-3.0 认领 讨论 1.2k 星数 是 中文 C 主语言 否 活跃 1 贡献者 10 Issues 否 组织 无 最新版本 207 Forks GPL-3.0 ...
becomes more tractable, can be solved in real-time on-board in a model predictive control fashion, and becomes robust against unpredicted disturbances. The reference motions are tracked by a hierarchical whole-body controller that sends torque commands to the robot.via/read more:mbjelonic.github ...
Fig. 4: Equipping the ULTIMAC on a bio-inspired legged robot: detection of terrain and analysis of gait. Full size image Fig. 5: Terrain type classification by machine learning. Full size image Discussion In summary, we developed a thin, flexible, lightweight, fast to respond, extremely sen...
This paper proposes to solve the problem of Vision-and-Language Navigation with legged robots, which not only provides a flexible way for humans to command but also allows the robot to navigate through more challenging and cluttered scenes. However, it is non-trivial to translate human language ...
ultimately facilitating more efficient behavior learning. Experimental results on tasks involving bipedal and quadrupedal robot motion control demonstrate that our method surpasses the performance of state-of-the-art LLM-based reward generation methods by over 37.6% in terms of human normalized score. Mor...