Gait study plays an important role in the walking robot, because it is the foundation of walking robots. The robot must first determine the walking pattern and rules, thus we can evolve further design, control, analysis or study. This research focus on hexapod and quadruped walking robots, and establishes a mathematical model which can fully describe natural and artificial gaits, and systematically plan and express them. Another point of this research is planning walk trajectory of robot. Here we purpose a new concept of foot trajectory planning, and establish S-V-A-J models for feet motion. We try to make robots move forward with constant velocity, as a goal, by using piecewise function of cam design theory. Therefore robot can walk with constant velocity and maintain the continuity of acceleration.

Legged robots are much difficult to design and control than wheeled robots. However, one of advantages of the legged robots is that they are move adaptable to rough terrains and the task of stepping over obstacles. The gait algorithm of a robot is an important job before components the configuration of the body and each leg. The main purpose of this thesis is to discuss leg failure in gait planning procedure for multi-legged robots with symmetric structures. The legs discussed herein are in the form of an articulated arm with three revolute joints. Various effects on motion characteristics due to different leg faults, such as robot¡¦s walking efficiency and stability are also investigated. On extreme conditions, the robot will cease to walk after a leg failure. In this work a scheme is proposed to transform the scrambled leg pattern to a better or even optimum configuration. This leg switching scheme can improve the stability of the robot when problematic legs are disconnected from the body.

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The Multi-Appendage Robotic System (MARS) built for this research is a hexapod robotic platform capable of walking and performing manipulation tasks. Each of the six limbs of MARS incorporates a three-degree of freedom (DOF), kinematically spherical proximal joint, similar to a shoulder or hip joint; and a 1-DOF distal joint, similar to an elbow or knee joint. Designing walking gaits for such multi-limb robots requires a thorough understanding of the kinematics of the limbs, including their workspace. The specic abilities of a walking algorithm dictate the usable workspace for the limbs. Generally speaking, the more general the walking algorithm is, the less constricted the workspace becomes. However, the entire limb workspace cannot be used in a continuous, statically stable, alternating tripedal gait for such a robot; therefore a subset of the limb workspace is dened for walking algorithms. This thesis develops MARS limb workspaces in the knee up conguration, and analyzes its limitations for walking on planar surfaces. The workspaces range from simple 2D geometry to complex 3D volumes. While MARS is a hexapedal robot, the tasks of dening the workspace and walking agorthm for all six limbs can be abstracted to a single limb using the constraint of a tripedal, statically stable gait. Based on understanding the behavior of an individual limb, a walking algorithm was developed to allow MARS to walk on level terrain. The algorithm is adaptive in that it continously updates based on control inputs. Open Tech developed a similar algorithm, based on a 2D workspace. This simpler algorithm developed resulted in smooth gait generation, with near-instantaneous response to control input. This accomplishment demonstrated the feasibility of implementing a more sophisticated algorithm, allowing for inputs of all six DOF: x and y velocity, z velocity or walking height, yaw, pitch and roll. This latter algorithm uses a 3D workspace developed to aord near-maximum step length. The workspace analysis and walking algorithm development in this thesis can be applied to the further advancement of walking gait generation algorithms. / Master of Science

La robotique humanoïde arrive a maturité avec des robots plus rapides et plus précis. Pour faire face à la complexité mécanique, la recherche a commencé à regarder au-delà du cadre habituel de la robotique, vers les sciences de la vie, afin de mieux organiser le contrôle du mouvement. Cette thèse explore le lien entre mouvement humain et le contrôle des systèmes anthropomorphes tels que les robots humanoïdes. Tout d’abord, en utilisant des méthodes classiques de la robotique, telles que l’optimisation, nous étudions les principes qui sont à la base de mouvements répétitifs humains, tels que ceux effectués lorsqu’on joue au yoyo. Nous nous concentrons ensuite sur la locomotion en nous inspirant de résultats en neurosciences qui mettent en évidence le rôle de la tête dans la marche humaine. En développant une interface permettant à un utilisateur de commander la tête du robot, nous proposons une méthode de contrôle du mouvement corps-complet d’un robot humanoïde, incluant la production de pas et permettant au corps de suivre le mouvement de la tête. Cette idée est poursuivie dans l’étude finale dans laquelle nous analysons la locomotion de sujets humains, dirigée vers une cible, afin d’extraire des caractéristiques du mouvement sous forme invariants. En faisant le lien entre la notion “d’invariant” en neurosciences et celle de “tâche cinématique” en robotique humanoïde, nous développons une méthode pour produire une locomotion réaliste pour d’autres systèmes anthropomorphes. Dans ce cas, les résultats sont illustrés sur le robot humanoïde HRP2 du LAAS-CNRS. La contribution générale de cette thèse est de montrer que, bien que la planification de mouvement pour les robots humanoïdes peut être traitée par des méthodes classiques de robotique, la production de mouvements réalistes nécessite de combiner ces méthodes à l’observation systématique et formelle du comportement humain. / Humanoid robotics is coming of age with faster and more agile robots. To compliment the physical complexity of humanoid robots, the robotics algorithms being developed to derive their motion have also become progressively complex. The work in this thesis spans across two research fields, human neuroscience and humanoid robotics, and brings some ideas from the former to aid the latter. By exploring the anthropological link between the structure of a human and that of a humanoid robot we aim to guide conventional robotics methods like local optimization and task-based inverse kinematics towards more realistic human-like solutions. First, we look at dynamic manipulation of human hand trajectories while playing with a yoyo. By recording human yoyo playing, we identify the control scheme used as well as a detailed dynamic model of the hand-yoyo system. Using optimization this model is then used to implement stable yoyo-playing within the kinematic and dynamic limits of the humanoid HRP-2. The thesis then extends its focus to human and humanoid locomotion. We take inspiration from human neuroscience research on the role of the head in human walking and implement a humanoid robotics analogy to this. By allowing a user to steer the head of a humanoid, we develop a control method to generate deliberative whole-body humanoid motion including stepping, purely as a consequence of the head movement. This idea of understanding locomotion as a consequence of reaching a goal is extended in the final study where we look at human motion in more detail. Here, we aim to draw to a link between “invariants” in neuroscience and “kinematic tasks” in humanoid robotics. We record and extract stereotypical characteristics of human movements during a walking and grasping task. These results are then normalized and generalized such that they can be regenerated for other anthropomorphic figures with different kinematic limits than that of humans. The final experiments show a generalized stack of tasks that can generate realistic walking and grasping motion for the humanoid HRP-2. The general contribution of this thesis is in showing that while motion planning for humanoid robots can be tackled by classical methods of robotics, the production of realistic movements necessitate the combination of these methods with the systematic and formal observation of human behavior.

This thesis addresses two important issues when operating the novel three legged mobile robot STriDER (Self-excited Tripedal Dynamic Experimental Robot); how to stand up after falling down while minimizing the motor torques at the joints and considerations for gait planning. STriDER uses a unique tripedal gait to walk with high energy efficiency and has the ability to change directions. In the first version of STriDER, the concept of passive dynamic locomotion was emphasized; however, for the new version, all joints are actively controlled for robustness. The robot is inherently stable when all three feet are on the ground due to its tripod stance, but it can still fall down if it trips while taking a step or if unexpected external forces act on it. The unique structure of STriDER makes the simple task of standing up challenging for a number of reasons; the high height of the robot and long limbs require high torque at the actuators due to its large moment arms; the joint configuration and length of the limbs limit the workspace where the feet can be placed on the ground for support; the compact design of the joints allows limited joint actuation motor output torque; three limbs do not allow extra support and stability in the process of standing up. This creates a unique problem and requires novel strategies to make STriDER stand up. This thesis examines five standing up strategies unique to STriDER: three feet pushup, two feet pushup, one foot pushup, spiral pushup, and feet slipping pushup. Each strategy was analyzed and evaluated considering constraints such as static stability, friction at the feet, kinematic configuration and joint motor torque limits to determine optimal design and operation parameters. Using the findings from the analysis, experiments were conducted for all five standing up strategies to determine the most efficient standing up strategy for a given prototype using the same design and operation parameters for each method. Also, a literature review was conducted for human standing from a chair and human pushup exercises and the conclusions were compared to the analysis presented in this thesis. Many factors contribute to the development of STriDER's gait. Several considerations for gait planning as the robot takes a step are investigated, including: stability, dynamics, the body's maximum and minimum allowable heights, the swing legs foot clearance to the ground, and the range of the subsequent swing foot contact positions. A static stability margin was also developed to asses the stability of STriDER. This work will lay the foundation for future gait generation research for STriDER. Additionally, guidelines for future work on single step gait generation based on kinematics and dynamics are discussed. The findings presented will advance the capabilities and adaptability of the novel robot STriDER. By studying standing up strategies and gait planning issues, the most efficient control methods can be implement for standing up and preparing to take a step and lay out the foundations for future research and development on STriDER. / Master of Science