Quadruped Robot Control: An Approach Using Body Planar Motion Control, Legs Impedance Control and Bézier Curves.

In robotics, the ability of quadruped robots to perform tasks in industrial, mining, and disaster environments has already been demonstrated. To ensure the safe execution of tasks by the robot, meticulous planning of its foot placements and precise leg control are crucial. Traditional motion planning and control methods for quadruped robots often rely on complex models of both the robot itself and its surrounding environment. Establishing these models can be challenging due to their nonlinear nature, often entailing significant computational resources. However, a more simplified approach exists that focuses on the kinematic model of the robot's floating base for motion planning. This streamlined method is easier to implement but also adaptable to simpler hardware configurations. Moreover, integrating impedance control into the leg movements proves advantageous, particularly when traversing uneven terrain. This article presents a novel approach in which a quadruped robot employs impedance control for each leg. It utilizes sixth-degree Bézier curves to generate reference trajectories derived from leg velocities within a planar kinematic model for body control. This scheme effectively guides the robot along predefined paths. The proposed control strategy is implemented using the Robot Operating System (ROS) and is validated through simulations and physical experiments on the Go1 robot. The results of these tests demonstrate the effectiveness of the control strategy, enabling the robot to track reference trajectories while showing stable walking and trotting gaits.

Kinematic and dynamic data from a robotic assembly of aeronautical threaded fasteners.

Industrial screwing is one of several industry branches' most common manufacturing processes. Good quality and structured data from these operations have increased demand with the popularization of data-driven techniques for manufacturing automation. The dataset presented in this paper comprises screwing experiments with aeronautical nuts performed by an industrial robot Kuka KR-16 in a lab setting. The data comprises force, torque, linear and angular displacements, and velocities in time-series format. The dataset contains three different experiment results: mounted, jammed, and not mounted, which can be used as labels for classification techniques.