Adaptive, fast walking in a biped robot under neuronal control and learning

Human walking is a dynamic, partly self-stabilizing process relying on the interaction of the biomechanical design with its neuronal control. The coordination of this process is a very difficult problem, and it has been suggested that it involves a hierarchy of levels, where the lower ones, e.g., interactions between muscles and the spinal cord, are largely autonomous, and where higher level control (e.g., cortical) arises only pointwise, as needed. This requires an architecture of several nested, sensori–motor loops where the walking process provides feedback signals to the walker's sensory systems, which can be used to coordinate its movements. To complicate the situation, at a maximal walking speed of more than four leg-lengths per second, the cycle period available to coordinate all these loops is rather short. In this study we present a planar biped robot, which uses the design principle of nested loops to combine the self-stabilizing properties of its biomechanical design with several levels of neuronal control. Specifically, we show how to adapt control by including online learning mechanisms based on simulated synaptic plasticity. This robot can walk with a high speed (> 3.0 leg length/s), self-adapting to minor disturbances, and reacting in a robust way to abruptly induced gait changes. At the same time, it can learn walking on different terrains, requiring only few learning experiences. This study shows that the tight coupling of physical with neuronal control, guided by sensory feedback from the walking pattern itself, combined with synaptic learning may be a way forward to better understand and solve coordination problems in other complex motor tasks

Visual Servoing

International audienceThis chapter introduces visual servo control, using computer vision data in the servo loop to control the motion of a robot. We first describe the basic techniques that are by now well established in the field. We give a general overview of the formulation of the visual servo control problem, and describe the two archetypal visual servo control schemes: image-based and pose-based visual servo control. We then discuss performance and stability issues that pertain to these two schemes, motivating advanced techniques. Of the many advanced techniques that have been developed , we discuss 2.5-D, hybrid, partitioned, and switched approaches. Having covered a variety of control schemes, we deal with target tracking and controlling motion directly in the joint space and extensions to under-actuated ground and aerial robots. We conclude by describing applications of visual ser-voing in robotics

Kinematic Visual Servo Control of a Quadrotor aerial vehicle

Visual systems are key sensors for control of small scale unmanned aerial vehicles. In this paper we investigate a range of image based visual servo control algorithms for positioning of flying vehicles capable of hover. The image based outer control loop for translation kinematics is coupled to a high-gain inner control loop that regulates translational velocities and full attitude dynamics. Zero and first order image moments are used as visual features for the control design. Perspective projection moments with suitable scaling along with a classical image based visual servo control design lead to satisfactory transients and asymptotic stability of the closed-loop system when the image plane remains parallel to the target. However, the system response may lack robustness for aggressive manoeuvres. In order to overcome this problem, several control schemes, based on spherical image moments, are designed and their performance is analysed. All designed control laws have been tested on a kinematic robotic manipulator to demonstrate the relative strengths and weaknesses of thedifferent image based visual servo control designs. The three most promising control algorithms have been successfully implemented on an autonomous aerial vehicle showing excellent performances in all three cases

Control of Nonprehensile Planar Rolling Manipulation: A Passivity-Based Approach

This paper presents a new procedure to design a control law using the classical interconnection and damping assignment technique within the passivity-based port-Hamiltonian framework. The sought goal is to reduce the complexity of solving the so-called matching equations. The proposed approach is applied to two case studies of planar rolling nonprehensile manipulation, namely, the ball-and-beam and the eccentric disk-on-disk. The performance of the resulting controllers is illustrated through both simulations and experimental results, showing the applicability of the design in a real setup

Visual Servoing in Robotics

Visual servoing is a well-known approach to guide robots using visual information. Image processing, robotics, and control theory are combined in order to control the motion of a robot depending on the visual information extracted from the images captured by one or several cameras. With respect to vision issues, a number of issues are currently being addressed by ongoing research, such as the use of different types of image features (or different types of cameras such as RGBD cameras), image processing at high velocity, and convergence properties. As shown in this book, the use of new control schemes allows the system to behave more robustly, efficiently, or compliantly, with fewer delays. Related issues such as optimal and robust approaches, direct control, path tracking, or sensor fusion are also addressed. Additionally, we can currently find visual servoing systems being applied in a number of different domains. This book considers various aspects of visual servoing systems, such as the design of new strategies for their application to parallel robots, mobile manipulators, teleoperation, and the application of this type of control system in new areas

Controlling a drone: Comparison between a based model method and a fuzzy inference system

International audienceThe work describes an automatically on-line self-tunable fuzzy inference system (STFIS) of a new configuration of mini-flying called XSF (X4 Stationnary Flyer) drone. A fuzzy controller based on on-line optimization of a zero order Takagi-Sugeno fuzzy inference system (FIS) by a back propagation-like algorithm is successfully applied. It is used to minimize a cost function that is made up of a quadratic error term and a weight decay term that prevents an excessive growth of parameters. Thus, we carried out control for the continuation of simple trajectories such as the follow-up of straight lines, and complex (half circle, corner, and helicoidal) by using the STFIS technique. This permits to prove the effectiveness of the proposed control law. Simulation results and a comparison with a static feedback linearization controller (SFL) are presented and discussed. We studied the robustness of the two controllers used in the presence of disturbances. We presented two types of disturbances, the case of a breakdown of an engine as well as a gust of wind

On the design of multi-platform parallel mechanisms

Parallel mechanisms have been examined in more and more detail over the past two decades. Parallel mechanisms are essentially the same design layout, a base, multiple legs/limbs, and a moving platform with a single end-effector to allow the mechanism to complete its desired function. Recently, several research groups have begun looking into multiple-platform parallel mechanisms and/or multiple end-effectors for parallel mechanisms. The reason for the research in this new form of parallel mechanism stems from multiple sources, such as applications that would require multiple handling points being accessed simultaneously, a more controlled gripper motion by having the jaws of the gripper being attached at different platforms, or to increasing the workload of the mechanism. The aim of the thesis is to modify the design process of parallel mechanisms so that it will support the development of a new parallel mechanism with multiple platforms capable of moving relative to each other in at least 1-DOF and to analyse the improvements made on the traditional single platform mechanism through a comparison of the power requirements for each mechanism. Throughout the thesis, a modified approach to the type synthesis of a parallel mechanism with multiple moving platforms is proposed and used to create several case study mechanisms. Additionally, this thesis presents a new series of methods for determining the workspace, inverse kinematic and dynamic models, and the integration of these systems into the design of a control system. All methods are vetted through case studies where they are judged based on the results gained from existing published data. Lastly, the concepts in this thesis are combined to produce a physical multi-platform parallel mechanism case study with the process being developed at each stage. Finally, a series of proposed topics of future research are listed along with the limitations and contributions of this work