Control

Legged robot research has been an active area of study since the late nineties. Let’s take a look at how we can generate walking trajectories for bipedal robots, using some of these ideas. The Objective: Implement a quick and dirty way of generating walking trajectories Constraints: Do it quickly. Minimize sophistication. Anything goes! What this post will cover: Overview of the minimal set of ideas required to develop walking algorithms Computation of bipedal joint trajectories for a simple walking gait What will not be covered: [Read More]

Let’s take a look at how we can set up a framework for streamlined simulation and hardware control of a manipulator. The robot under consideration is Ufactory’s Lite6 manipulator and the simulation/setup tool used is Drake. All the code used in this post can be found in my repo. But before we start, some explanations are in order. Lite6? The Lite6 is one of the more economical (not to be confused with cheap) manipulators one can buy, especially for personal research where you’re not going to be spending tens of thousands of dollars on some of the more well established robots out there. [Read More]

TrajOpt $[1]$ is an optimization based approach for motion planning. More specifically, it uses a sequential convex optimization procedure along with a formulation of collision constraints to find locally optimal planning trajectories, even for robotic systems that have a large number of degrees of freedom. This post will go into the details of the optimization part, and give an outline of how it can be implemented. My implementation can be found here [Read More]