Fixing Kinova Gen3 Robot Arm Instability

Jan 15, 2026 by Editorial Team 41 views

Hey guys, let's dive into a common issue when working with the Kinova Gen3 robot arm in the MuJoCo simulator: physical instability. If you've ever spawned this robot and watched it go haywire, oscillating wildly or even exploding, you're in the right place! I've been wrestling with this problem and wanted to share my findings and the solutions I've come up with to stabilize the Gen3 arm.

The Problem: Uncontrollable Oscillations

So, the main issue? The Kinova Gen3, right out of the box in the MuJoCo simulation, often exhibits violent oscillations. These are especially noticeable in joints 3 and 7. Basically, the arm starts bouncing around like a kid on a trampoline. This is a real bummer because you can't even begin to control the robot when it's constantly jittering. Sometimes, it's so bad that the arm basically explodes, with parts flailing about uncontrollably. This happens even before you've given the arm any commands or introduced any external forces. It's all internal dynamics gone wrong!

I've included a video demonstrating the issue. You can see the arm going wild immediately after it appears in the environment. It's like it has a mind of its own, but not in a good way! I spent some time tinkering with the XML file, and I've found a combination of adjustments that seem to work. It took some serious trial and error to figure out how to tame this beast, but finally, I managed to get it stable enough to teleoperate as shown in the second video.

My Solutions: A Step-by-Step Approach

After a lot of experimentation, I've come up with a few key adjustments that significantly improve the stability of the Kinova Gen3 arm. Here's what I did:

1. Re-tuning Actuator Classes: Getting the Actuators Right

The first thing I focused on was the robot's actuators. In MuJoCo, these are responsible for controlling the robot's joints. The default settings were causing some serious overshoots and oscillations. I had to dial these settings back quite a bit. Basically, the original settings were too aggressive.

Large Actuators: I reduced the proportional gain ( $k_p$ ) from 2000 to 500. And I also decreased the derivative gain ( $k_v$ ) from 100 to 20. These adjustments helped to dampen the initial response of the large joints, preventing them from overreacting and causing those crazy oscillations.
Small Actuators: For the smaller, more agile joints, I decreased $k_p$ from 500 to 100 and $k_v$ from 50 to 2. This was especially important for the wrist joints, which have lower inertia. By reducing these gains, I prevented the wrist from becoming too twitchy and contributing to the instability. The main goal here was to find a balance between responsiveness and stability. Too much gain, and you get oscillations; too little, and the robot becomes sluggish.

2. Joint Regularization: Adding Stability to the Joints

Next, I added some crucial properties to the <joint> tags within the XML file. These properties help the solver handle the high-frequency dynamics and improve overall stability.

Armature (0.1): I set an armature value of 0.1. The armature essentially adds inertia to the joints. This helps to provide more stability and prevent the joints from reacting too violently to small forces or disturbances. Think of it like adding weight to a spinning top – it makes it more resistant to wobbling.
Damping (1.0): I set a damping value of 1.0. Damping introduces internal resistance to the joints. It helps to dissipate energy and prevent oscillations from building up over time. It's like adding friction to the joints, slowing them down slightly and helping them settle into their desired positions. It's a key factor in keeping everything nice and smooth.

3. Contact Exclusions: Preventing Self-Collisions

Finally, I addressed the issue of self-collisions. In the default configuration, the robot's links can collide with each other. This can generate unexpected forces and contribute to instability. I added explicit exclusions to the XML file to prevent these self-collisions, focusing on links that are physically connected or adjacent.

I added a series of <exclude> tags within the <contact> section of the XML file. These tags tell MuJoCo to ignore collisions between specific body pairs. Here's a snippet of the exclusions I added:

<contact>
  <exclude body1="base_link" body2="shoulder_link"/>
  <exclude body1="shoulder_link" body2="half_arm_1_link"/>
  <exclude body1="half_arm_1_link" body2="half_arm_2_link"/>
  <exclude body1="half_arm_2_link" body2="forearm_link"/>
  <exclude body1="forearm_link" body2="spherical_wrist_1_link"/>
  <exclude body1="spherical_wrist_1_link" body2="spherical_wrist_2_link"/>
  <exclude body1="spherical_wrist_2_link" body2="bracelet_link"/>
</contact>

This is like putting up invisible barriers between the robot's parts to stop them from bumping into each other. These are the main culprits for causing those annoying vibrations. By preventing these collisions, you reduce the chances of unexpected forces that can throw the arm off balance. This made a significant difference in smoothing out the robot's behavior. I specifically excluded collisions between the base and shoulder, the shoulder and the first part of the arm, and so on, all the way to the wrist.

Combining the Fixes and Final Results

I tried out a combination of these fixes, and the approach outlined here is what ultimately worked for me. The key was to adjust all the settings in concert to create a stable, responsive system. You can find my final, working gen3_fixed.xml file. It includes all the adjustments described above. You can grab it, load it into your MuJoCo environment, and see the difference for yourself.

Important Considerations and Further Tuning

Remember, the optimal values for $k_p$ , $k_v$ , armature, and damping might vary depending on your specific simulation environment and the desired behavior of the robot. Therefore, it is important that you adjust these parameters based on your experiment. I highly encourage you to experiment with these settings and fine-tune them to suit your application and performance goals. If you're working with a real-world robot or a more complex simulation, you might need to further tune these parameters.

Conclusion: Achieving Stability for Kinova Gen3

Getting the Kinova Gen3 arm to behave in MuJoCo can be a bit tricky, but it's totally manageable once you know the right levers to pull. I hope that these tips are helpful for you guys. By retuning the actuators, adding joint regularization, and preventing those annoying self-collisions, you can tame the wild oscillations and get your robot arm working smoothly. Give these adjustments a shot, and let me know how it goes! If you have any further questions or suggestions, please feel free to share them in the comments below. Happy simulating!