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FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARs SENSE: Stereo OpEN Vocabulary SEmantic Segmentation Continual Hand-Eye Calibration for Open-world Robotic Manipulation PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology $π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities R3D: Revisiting 3D Policy Learning Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand 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mc-mujoco: Simulating Articulated Robots with FSM Controllers in MuJoCo
Rohan P. Singh, Pierre Gergondet, Fumio Kanehiro · 2022-09-01 · via cs.RO updates on arXiv.org

For safe and reliable deployment of any robot controller on the real hardware platform, it is generally a necessary practice to comprehensively assess the performance of the controller with the specific robot in a realistic simulation environment beforehand. While there exist several software solutions that can provide the core physics engine for this purpose, it is often a cumbersome and error-prone effort to interface the simulation environment with the robot controller being evaluated. The controller may have a complex structure consisting of multiple states and transitions within a finite-state machine (FSM), and may even require input through a GUI. In this work, we present mc-mujoco -- an open-source software framework that forms an interface between the MuJoCo physics simulator and the mc-rtc robot control framework. We provide implementation details and describe the process for adding support for essentially any new robot. We also demonstrate and publish a sample FSM controller for bipedal locomotion and stable grasping of a rigid object by the HRP-5P humanoid robot in MuJoCo. The code and usage instructions for mc-mujoco, the developed robot modules, and the FSM controller are available online.