Fast moving of a population of robots through a complex scenario

Swarm robotics consists in using a large number of coordinated autonomous robots, or agents, to accomplish one or more tasks, using local and/or global rules. Individual and collective objectives can be designed for each robot of the swarm. Generally, the agents' interactions exhibit a high degree of complexity that makes it impossible to skip nonlinearities in the model. In this paper, is implemented both a collective interaction using a modified Vicsek model where each agent follows a local group velocity and the individual interaction concerning internal and external obstacle avoidance. The proposed strategies are tested for the migration of a unicycle robot swarm in an unknown environment, where the effectiveness and the migration time are analyzed. To this aim, a new optimal control method for nonlinear dynamical systems and cost functions, named Feedback Local Optimality Principle - FLOP, is applied

A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots

This paper contributes towards the development and comparison of Divergent-Component-of-Motion (DCM) based control architectures for humanoid robot locomotion. More precisely, we present and compare several DCM based implementations of a three layer control architecture. From top to bottom, these three layers are here called: trajectory optimization, simplified model control, and whole-body QP control. All layers use the DCM concept to generate references for the layer below. For the simplified model control layer, we present and compare both instantaneous and Receding Horizon Control controllers. For the whole-body QP control layer, we present and compare controllers for position and velocity control robots. Experimental results are carried out on the one-meter tall iCub humanoid robot. We show which implementation of the above control architecture allows the robot to achieve a walking velocity of 0.41 meters per second.Comment: Submitted to Humanoids201

The Wheelbot: A Jumping Reaction Wheel Unicycle

Combining off-the-shelf components with 3Dprinting, the Wheelbot is a symmetric reaction wheel unicycle that can jump onto its wheels from any initial position. With non-holonomic and under-actuated dynamics, as well as two coupled unstable degrees of freedom, the Wheelbot provides a challenging platform for nonlinear and data-driven control research. This paper presents the Wheelbot's mechanical and electrical design, its estimation and control algorithms, as well as experiments demonstrating both self-erection and disturbance rejection while balancing.Comment: 8 pages, 13 figures, 2 tables, Accepted final version to appear in IEEE Robotics and Automation Letter

Design and simulate of LQR-Fuzzy controller for unicycle robot with double flywheels

This research is focus on design and simulate unicycle robot with double flywheels model with LQR-Fuzzy controller. Roll balancing torque is generated by gyroscopic effect. Pitch balancing torque is applied by inverted pendulum concept. To control the heading of the robot, the angular momentum from both flywheel is applied to control this. The robot model is based on Euler-Lagrange equations. The non-linear model is linearization by Taylor series expansion. The simulation results conducted by MATLAB/Simulink. LQR-Fuzzy is combination algorithm between LQR and Fuzzy controller. The main structure control is the LQR controller and use the Fuzzy controller to adjust the close loop controller gain. The simulation results is simulated and compared with conventional LQR