Robot Trotting with Segmented Legs in Simulation and Hardware.

This research is focusing on the implementation, testing, and analysis of quadrupedal, bio-inspired robot locomotion. Our tool of research is a light-weight, quadruped robot of the size of a house cat, both in simulation and hardware. We are currently following the idea of testing bio-inspired blue-prints such as leg-segmentation, directional leg compliance (bio-mechanical), and central pattern generators (bioinspired neuro-control) for their feasibility, and advantages against more traditional, engineered solutions. Clearly, our ﬁrst goal would be to reach a same level of performance as animals, e.g. in terms of speed, cost of transport, or versatility. Much research has been done on bio-mechanical and neuro-physiological research on legged vertebrates. Hence, data is available for animal locomotion such as gait patterns, speed, cost of transport, duty factor, joint angles, torque patterns, body angles, and ground reaction force (GRF) data. While this data allows one to study a subset of locomotion characteristics, it often lacks an intuitive way to compare animals of different species, or as for us, quadruped robots. We started applying the collision angle analysis (Lee, Bertram, et al. 2011) for trot gait, based on qualitative and quantitative results from goats and dogs (taken from (ibid.)), and experimental recordings of our robot’s center of mass (COM) and GRF.

Pattern Generation for Rough Terrain Locomotion with Quadrupedal Robots

Mostafa Ajallooeian

Animals are able to locomote on rough terrain without any apparent difficulty, but this does not mean that the locomotor system is simple. The locomotor system is actually a complex multi-input multi-output closed-loop control system. This thesis is dedicated to the design of controllers for rough terrain locomotion, for animal-like quadrupedal robots. We choose the problem of blind rough terrain locomotion as the target of experiments. Blind rough terrain locomotion requires continuous and momentary corrections of leg movements and body posture, and provides a proper testbed to observe the interaction of different mod- ules involved in locomotion control. As for the specific case of this thesis, we have to design rough terrain locomotion controllers that do not depend on the torque-control capability, have limited sensing, and have to be computationally light, all due to the properties of the robotics platform that we use. We propose that a robust locomotion controller, taking into account the aforementioned constraints, is constructed from at least three modules: 1) pattern generators providing the nominal patterns of locomotion; 2) A posture controller continuously adjusting the attitude of the body and keeping the robot upright; and 3) quick reflexes to react to unwanted momentary events like stumbling or an external force impulse. We introduce the framework of morphed oscillators to systematize the design of pattern gen- erators realized as coupled nonlinear oscillators. Morphed oscillators are nonlinear oscillators that can encode arbitrary limit cycle shapes and simultaneously have infinitely large basins of attraction. More importantly, they provide dynamical systems that can assume the role of feedforward locomotion controllers known as Central Pattern Generators (CPGs), and accept discontinuous sensory feedback without the risk of producing discontinuous output. On top of the CPG module, we add a kinematic model-based posture controller inspired by virtual model control (VMC), to control the body attitude. Virtual model control produces forces, and through the application of the Jacobian transpose method, generates torques which are added to the CPG torques. However, because our robots do not have a torque- control capability, we adapt the posture controller by producing task-space velocities instead of forces, thus generating joint-space velocity feedback signals. Since the CPG model used for locomotion generates joint velocities and accepts feedback without the fear of instability or discontinuity, the posture control feedback is easily integrated into the CPG dynamics. More- over, we introduce feedback signals for adjusting the posture by shifting the trunk positions, which directly update the limit cycle shape of the morphed oscillator nodes of the CPG. Reflexes are added, with minimal complexity, to react to momentary events. We implement simple impulse-based feedback mechanisms inspired by animals and successful rough terrain robots to 1) flex the leg if the robot is stumbling (stumbling correction reflex); 2) extend the leg if an expected contact is missing (leg extension reflex); or 3) initiate a lateral stepping sequence in response to a lateral external perturbation. CPG, posture controller, and reflexes are put together in a modular control architecture alongside additional modules that estimate inclination, control speed and direction, maintain timing of feedback signals, etc. [...]

EPFL2015

A Control and Optimization Framework for Robot Locomotion

Soha Pouya

Despite great efforts in designing legged robots, we are still far from the adaptivity, efficiency and robustness with which animals can move. Observations from successful biomimetic designs highlight the significant role of clever morphological design in achieving such performance. In addition, the important role of the controller in improving the locomotion performance is undoubtable. In fact, there is a complex link between morphology and motor control of locomoting systems. In animals’ locomotion, there is a large number of evidence showing the effective link between their morphology and functionality. Motivated by biological observations, similar questions can be posed from a robotics perspective: “what are the relative and complementary roles of robot control and morphology (similar to animal’s brain and body) in the generated locomotor behavior?”, and more pragmatically, “how can we take lessons from these observations to reduce the current gap between robots’ locomotion performance and what is observed in their biological counterparts?”. These are the fundamental questions that have motivated studies in this thesis. While empirical studies are essential to address aforementioned questions, they require simplifying contexts to yield insightful predictions and examinable theories. Both theoretical and physical models (i.e. simulations and robots) can significantly contribute in providing such insights. While robot experiments are essential to evaluate and explore the involved biological concept, they are usually time-consuming and costly. Hence, it would be advantageous if one could exploit the power of theoretical models for development of ideas and hypotheses before their implementation on the real robot. In this thesis, we aim at leveraging the strength of theoretical models to study the above-mentioned questions, namely, the relative role of control and morphology in improving the robot locomotion functionalities. To provide useful theoretical models, we take a step-wise approach, where we start from model-free methods and proceed with advancing the locomotion control by incorporating dynamics models at different levels of complexity. In particular, we develop a pool of robot models, starting from a simplified massless leg to a detailed dynamics model of the leg, to a 2D quadruped with spine joint and eventually to a 3D detailed dynamics model of a quadruped. Along with developing dynamics model of the robot, we devise a set of control and optimization techniques with the main goal of improving locomotion performance. There are several performance criteria to consider (such as energy efficiency, maneuverability, adaptivity to unknown terrains) and a key question is how to build the control architecture to hold a proper trade-off between these partially contradicting criteria. We take advantage of the developed dynamic models in both (i) improving the controller performance and (ii) implementing analytical tools to evaluate and compare different locomotion performance criteria. The central outcome of this thesis is a bio-inspired modeling, control, and optimization framework for legged robot locomotion, which is evaluated on a set of robots with different morphologies. In all cases, we explore how the locomotion performance can be improved by introducing new control techniques or be influenced by the morphological aspects (such as joint configuration and mass distribution). In particular, we show the effect of using more detailed dynamics model to improve the predictive performance of the simulations both for analyzing morphological factors and for robustness of the controller to internal (e.g. change in the inertial parameters) and external (e.g. walking on rough terrains) perturbations. The framework is generic and is used to model, control and analyze locomotion gaits for three compliant quadruped robots (Locomorph, Cheetah-Cub and Bobcat robots) and a modular robot (Roombots).

EPFL2013

Shoaling with fish: using miniature robotic agents to close the interaction loop with groups of zebrafish Danio rerio

Frank Bonnet

Robotic animals are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. The miniaturization of technologies and the increase in performance of embedded systems allowed engineers to develop more powerful, sophisticated and miniature devices. The case of robotic fish is a typical example of such challenging design: the fish locomotion and body movements are difficult to reproduce and the device has to move autonomously underwater. More specifically, in the case of collective animal behavior research, the robotic device has to interact with animals by generating and exploiting signals relevant for social behavior. Once perceived by the animal society as conspecific, these robots can become powerful tools to study the animal behaviors, as they can at the same time monitor the changes in behavior and influence the collective choices of the animal society. In this work, we present novel robotized tools that can integrate shoals of fish in order to study their collective behaviors. This robotic platform is composed of two subsystems: a miniature wheeled mobile robot that can achieve dynamic movements and multi-robot long-duration experiments, and a robotic fish lure that is able to beat its tail to generate fish-like body movements. The two subsystems are coupled with magnets which allows the wheeled mobile robot to steer the robotic fish lure so that it reaches very high speeds and accelerations while achieving shoaling. An experimental setup to conduct studies on mixed societies of artificial and living fish was designed to facilitate the experiments for biologists. A software framework was also implemented to control the robots in a closed-loop using data extracted from visual tracking that retrieved the position of the robots and the fish. We selected the zebrafish Danio rerio as a model to perform experiments to qualify our system. We used the current state of the art on the zebrafish social behavior to define the specifications of the robots, and we performed stimuli analysis to improve their developments. Bio-inspired controllers were designed based on data extracted from experiments with zebrafish for the robots to mimic the zebrafish locomotion underwater. Experiments involving a robot with a shoal of fish in a constrained environment showed that the locomotion of the robot was one of the main factor to affect the collective behavior of zebrafish. We also shown that the body movements and the biomimetic appearance of the lure could increase its acceptance by fish. Finally, an experiment involving a mixed society of fish and robots qualified the robotic system to be integrated among a zebrafish shoal and to be able to influence the collective decisions of the fish. These results are very promising for the field of fish-robot interaction studies, as we showed the effect of the robots in long-duration experiments and repetitively, with the same order of response from the animals.

EPFL2017