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a blog for things I encounter while coding and researching neuroscience, motor control, and learning

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Spiking neural networks take control

Back in September I had an review article in Science Robotics published, discussing new work from Abadia et al, 2021 titled A cerebellar-based solution to the nondeterministic time delay problem in robotic control. In my review I talk about the parallel’s between the brain inspired approach Abadia et al used to create a neural circuit that can effectively...

ABR Control supports Mujoco!

https://github.com/abr/abr_control And it has for a while, actually. ‘Oh great’, you may be thinking, ‘but I can never afford the Mujoco license, I’m not a tenured professor!’Well fear not, friends! Mujoco recently became free for all to use! You can now download their public license and be on your merry way. The associated downside is there’s...

Adaptive neurorobotics using Nengo and the Loihi

I gave a talk last month at the HALO (Harware and Algorithms for Learning On-achip) workshop at ICCAD (the International Conference on Computed Aided Design). It’s goes over the work from our paper that came out in Frontiers in Neurorobotics in October, titled: Nengo and Low-Power AI Hardware for Robust, Embedded Neurorobotics. I’ve put it up on YouTube,...

Building models in Mujoco

Mujoco is an awesome simulation tool. You’re probably familiar with it from it’s use in the OpenAI gym, or from it featuring in articles and videos on model predictive control and robots learning to walk research. If you’re not familiar with it, you should check it out! Mujoco provides super fast dynamics simulation with a focus on contact dynamics....

Converting your Keras model into a spiking neural network

Let’s set the scene: You know Keras, you’ve heard about spiking neural networks (SNNs), and you want to see what all the fuss is about. For some reason. Maybe it’s to take advantage of some cool neuromorphic edge AI hardware, maybe you’re into computational modeling of the brain, maybe you’re masochistic and like a challenge, or you just think SNNs...

Force control of task-space orientation

So you want to use force control to control the orientation of your end-effector, eh? What a noble endeavour. I, too, wished to control the orientation of the end-effector. While the journey was long and arduous, the resulting code is short and quick to implement. All of the code for reproducing the results shown here is up on my GitHub and in the ABR...

Natural policy gradient in TensorFlow

In working towards reproducing some results from deep learning control papers, one of the learning algorithms that came up was natural policy gradient. The basic idea of natural policy gradient is to use the curvature information of the of the policy’s distribution over actions in the weight update. There are good resources that go into details about...

Building a spiking neural model of adaptive arm control

About a year ago I published the work from my thesis in a paper called ‘A spiking neural model of adaptive arm control’. In this paper I presented the Recurrent Error-driven Adaptive Control Hierarchy (REACH) model. The goal of the model is to begin working towards reproducing behavioural level phenomena of human movement with biologically plausible...

Matplotlib legends for mean and confidence interval plots

When plotting means and confidence intervals, sometimes the mean lines are hard to see and it’s nice to have included in your legend the color of the confidence interval shading. It turns out this is a bit of a chore in Matplotlib, but building off of their online examples you can get something that looks pretty alright: So here’s code for getting...

ABR Jaco repo public release!

https://github.com/abr/abr_jaco2 We’ve been working with Kinova’s Jaco arm with joint torque sensors for the last year or so as part of our research at Applied Brain Research, and we put together a fun adaptive control demo and got to show it to Justin Trudeau. As you might have guessed based on previous posts, the robotic control used force control....

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