Everything listed in this article is framed as a software problem, but the beauty of robotics is that many problems can fall to either software, hardware, or el

Everything listed in this article is framed as a software problem, but the beauty of robotics is that many problems can fall to either software, hardware, or electrical solutions. Without further ado, a very incomplete list of hardware and electrical innovations that would push robotics forward. - Cheaper and smaller low-backlash actuators. Motors and associated gearboxes are big, heavy, and expensive, which is a big part of why our robots have singularities in their designs, making the motion planning problem more difficult. - Actuators with good force-speed curves. Muscles have both great torque at zero speed and great speed at zero torque. (weight lifting and throwing a baseball). Only hydraulics come close to matching both numbers, and they're heavy, expensive, and tend to leak oil on the carpet. - Cheaper force/torque sensors. Most robots today don't even have torque sensing on all their actuators, let alone the sort of dense 6dof-sensing full-body surfaces that animal skin provides. - Across-the-board robustness improvements. Robots more mechanically complicated than a quadcopter tend to break a lot. This makes approaches like training ML models directly on hardware difficult. - Reliably low-latency wireless. There's been a lot of hype about cloud robotics, and there's a lot of potential in offboard sensing, but we need a cheap communication system that can deliver <30ms latency for those systems to work reliably. WiFi is great until you pass through a metal doorway and the signal degrades for 200ms. - Cheap and light lidars: true depth sensing with long range that works outside means a lot of hard computer vision problems get easier, and means your robot can be smaller since it needs fewer cameras The thing I love about working in robotics is that we don't need to solve all the software problems and all the hardware problems to make a system that works well in the real world. We get to pick and choose which is easier, and often the solutions in software space depend intimately on the kind of substrate they need to run on.