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Need controls advice: My 28-DOF simulated primate robot has arm joint-angle jumps in MuJoCo (Open Source)
Hey everyone, I've been building CARL, an embodied virtual primate scout in MuJoCo. He has a 28-DOF body, 3-fingered hands, and is controlled by a multi-tiered biologically-inspired cognitive architecture. The codebase is fully open-source, but it is far from perfect. We are looking for help, critiques, and design upgrades on absolutely everything: 🛠️ 1. Physical Design & Body Upgrades (Morphology/Hardware) - Suggestions for better hand/gripper layouts (should we go to 5-fingers or use compliant pads?). - Better limb length proportions to maximize reach and avoid joint locking. - Optimal positioning of LiDAR, camera sensors, and tactile grids. - Bipedal chassis balancing and layout suggestions. 🎮 2. Control Loops & Trajectories (Robotics/Controls) - Smother arm trajectory models to fix our sudden joint-angle jumps and snapping. - Calibrating physics contact constraints in MuJoCo to stop fingertip clipping. - Alternatives to our current Damped Least Squares IK solver. 🧠 3. Cognitive Architecture & AI Models (Deep Learning/RL) - Optimizing our PPO actor-critic network and Liquid Time-Constant (LTC) arm policy. - Better reward shaping to speed up learning convergence (currently too slow!). - Improving how our high-level emotional drives (dopamine, cortisol) link down to motor execution. We are completely open to any feedback, design overhauls, or code contributions. Take a look at the repo and tell us what you would change! * GitHub Link: https://github.com/Manassadashiv/carl-simulation * Honest breakdown of our struggles: https://github.com/Manassadashiv/carl-simulation/blob/main/CONTRIBUTING.md submitted by /u/Manas_Sadashiv [link] [Kommentare] reddit.com · reddit.com
Hey everyone, I've been building CARL, an embodied virtual primate scout in MuJoCo. He has a 28-DOF body, 3-fingered hands, and is controlled by a multi-tiered biologically-inspired cognitive architecture. The codebase is fully open-source, but it is far from perfect. We are looking for help, critiques, and design upgrades on absolutely everything: 🛠️ 1. Physical Design & Body Upgrades (Morphology/Hardware) - Suggestions for better hand/gripper layouts (should we go to 5-fingers or use compliant pads?). - Better limb length proportions to maximize reach and avoid joint locking. - Optimal positioning of LiDAR, camera sensors, and tactile grids. - Bipedal chassis balancing and layout suggestions. 🎮 2. Control Loops & Trajectories (Robotics/Controls) - Smother arm trajectory models to fix our sudden joint-angle jumps and snapping. - Calibrating physics contact constraints in MuJoCo to stop fingertip clipping. - Alternatives to our current Damped Least Squares IK solver. 🧠 3. Cognitive Architecture & AI Models (Deep Learning/RL) - Optimizing our PPO actor-critic network and Liquid Time-Constant (LTC) arm policy. - Better reward shaping to speed up learning convergence (currently too slow!). - Improving how our high-level emotional drives (dopamine, cortisol) link down to motor execution. We are completely open to any feedback, design overhauls, or code contributions. Take a look at the repo and tell us what you would change! * GitHub Link: https://github.com/Manassadashiv/carl-simulation * Honest breakdown of our struggles: https://github.com/Manassadashiv/carl-simulation/blob/main/CONTRIBUTING.md submitted by /u/Manas_Sadashiv [link] [Kommentare]
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