Bio-inspired Flying Robots: Experimental Synthesis of Autonomous Indoor Flyers

This book demonstrates how bio-inspiration can lead to fully autonomous flying robots without relaying on external aids. Most existing aerial robots fly in open skies, far from obstacles, and rely on external beacons – mainly GPS – to localise and navigate. However, these robots are not able to fly at low altitude or in confined environments, and yet this poses absolutely no difficulty to insects. Indeed, flying insects display efficient flight control capabilities in complex environments despite their limited weight and relatively tiny brain size. From sensor suite to control strategies, the literature on flying insects is reviewed from an engineering perspective in order to extract useful principles that are then applied to the synthesis of artificial indoor flyers. Artificial evolution is also utilised to search for alternative control systems and behaviours that match the constraints of small flying robots. Specifically, the basic sensory modalities of insects, vision, gyroscopes and airflow sense, are applied to develop navigation controllers for indoor flying robots. These robots are capable of mapping sensor information onto actuator commands in real time to maintain altitude, stabilize the course and avoid obstacles. The most prominent result of this novel approach is a 10-gram microflyer capable of fully autonomous operation in an office-sized room using fly-inspired vision, inertial and airspeed sensors. This book is intended for all those interested in the autonomous robotics, working both in academic and industrial settings.

Designing a socially integrated mobile robot for ethological research

Jean-Louis Deneubourg, Alexey Gribovskiy, Francesco Mondada

A robot introduced into an animal group, accepted by the animals as conspecifics, and capable of interacting with them is an ecient tool for ethological research, particularly in studies of collective and social behaviour. In this paper, we present the implementation of an autonomous mobile robot developed by the authors to study group behaviour of chicks of the domestic chicken (Gallus gallus domesticus). We discuss the design of the robot and of the experimental framework that we built to run animal-robot experiments. The robot design was experimentally validated, we demonstrated that the robot can be socially integrated into animal groups. The designed system extends the current state of the art in the field of animal-robot interaction in general and the birds study in particular by combining such advantages as (1) the robot being a part of the group, (2) the possibility of mixed multi-robot, multi-animal groups, and (3) close-loop control of robots. It opens new opportunities in the study of behaviour in domestic fowl by using mobile robots; being socially integrated into the animal group, robots can profit from the positive feedback mechanism that plays key roles in animal collective behaviour. They have potential applications in various domains, from pure scientific research to applied areas such as control and ensuring welfare of poultry.

2018

Bio-inspired vision-based flying robots

Jean-Christophe Zufferey

There are not yet autonomous flying robots capable of manoeuvring in small cluttered environments as insects do. Encouraged by this observation, this thesis presents the development of ultra-light flying robots and control systems going one step toward fully autonomous indoor aerial navigation. The substantial weight and energy constraints imposed by this indoor flying robots preclude the use of powerful processors and active distance sensors. Moreover, flying systems require fast sensory-motor mapping despite their limited processing power. In order to cope with those apparently contradictory constraints, our approach takes inspiration from flying insects, which display efficient flight control capability in complex environments in spite of their limited weight and relatively tiny brain. In particular, they are able to stabilise their course, avoid obstacles and control their altitude, which represents the basic mechanisms we want to have on an indoor flying robot. To achieve efficient flight control, insects rely essentially on two sensory modalities: vision and gyroscope. They possess two low-resolution, compound eyes which are particularly sensitive to image motion (optic flow). In their visual system, some neurons are known to be responsible for detecting self-motion and impending collisions based on optic-flow. Gyroscopic information coming from two mechanosensors located behind the wings complements visual cues in tasks such as gaze and course stabilisation. In this thesis, we explore the application of such biological principles to develop navigation controllers for indoor flying robots. In particular, we address the problem of how low-resolution vision and gyroscopic information can be mapped into actuator commands in real-time to maintain altitude, stabilise the course and avoid obstacles. As an alternative to hand-crafting control systems based on biological principles, in a second phase, we take inspiration from the evolutionary process that eventually generated those animals and apply artificial evolution to search for alternative control systems and behaviours that can fit the constraints of indoor flying robots. Instead of replicating the biomechanics of insect flight, our targeted robotic platform is a fixed-wing airplane capable of flying indoors at very low speed (

EPFL2005

Control of Contact Tasks in Autonomous and Human-Robot Collaborative Scenarios: A Dynamical System Approach

Walid Amanhoud

Robotic systems are more and more present in our daily life. Robots became indeed more economical, easy to program, safe and collaborative in their interaction with humans, versatile in performing different tasks and adaptive towards changes in the environment. Despite the recent advances in robotics, developingfully autonomous robots to achieve complex industrial or daily-life tasks is still very challenging. The human, due to his superior perception, understanding and reasoning skills, especially in uncertain environment, needs to be in the loop. Therefore, the ability of robots to collaborate with humans is of great interest inthe robotics community. Human-Robot Collaboration usually implies robots that share the control of the tasks with humans, providing adjustable autonomy level and mutual adaptation. A field that can particularly benefits from such collaboration is assistive robotics surgery. The introduction of shared autonomyin surgical tasks has several advantages. In particular, it can provide higher accuracy, flexibility, control and efficiency during the operation, over longer time periods, relieve the surgeon during repetitive tasks and reduce his mental workload. However, it is not very clear how to best use shared control to assist asurgeon during the operation. As part of a research project (the "Surgical project"), in this thesis we would like to propose solutions to that problem by building a teleoperated shared control architecture for a laparoscopic surgery scenario. While laparoscopic surgery usually involves one surgeon and two humanassistants to perform the surgery, the project aims to replace the assistants by two partially teleoperated robotic systems. The target shared control architecture would explore various strategies to ensure safety for both the patient and the surgeon, provide accuracy and stability in motion and force control of the toolsattached to the robots, reduce the mental workload of the surgeon and adapt the level of assistance based on well-identified criteria.The first year was mainly devoted to the control of motion and force for contact tasks which is of great importance in the context of the project. Robot force control is traditionally achieved either explicitly through hybrid position/force control or implicitly using impedance control. We propose an approach leveraging theproperties of dynamical systems (DS) for immediate re-planning and robustness to real-time perturbations by exploiting local modulation of the DS. Dynamical systems has been widely used as a tool to represent and generate motion in robotics application. Here the idea is to propose a DS formulation to generatecontact force in addition to motion. First implementation and experiments to evaluate the effectiveness of the strategy were conducted in practice with a 7-DOF robotic arm (KUKA LWR IV+).So far we focused on contact tasks that were performed autonomously by one or two robots. Future work will improve and use the proposed DS approach to consider contact tasks in shared control scenarios where one human and one or two robots need to collaborate to successfully achieve the tasks. Because of the nature of the surgical project we will use teleoperation systems to introduce the human in the loop. The developed teleoperated shared control architecture will be evaluated on laparoscopic surgery related tasks.