Generalization of Optimal Motion Trajectories for Bipedal Walking

Abstract— Control of robot locomotion profits from the use of pre-planned trajectories. This paper presents a way to generalize globally optimal and dynamically consistent trajectories for cyclic bipedal walking. A small task-space consisting of stride-length and step time is mapped to spline parameters which fully define the optimal joint space motion. The paper presents the impact of different machine learning algorithms for velocity and torque optimal trajectories with respect to optimality and feasibility. To demonstrate the usefulness of the trajectories, a control approach is presented that allows general walking including transitions between points in the task-space

Generalization of optimal motion trajectories for bipedal walking

Abstract— Control of robot locomotion profits from the use of pre-planned trajectories. This paper presents a way to generalize globally optimal and dynamically consistent trajectories for cyclic bipedal walking. A small task-space consisting of stride-length and step time is mapped to spline parameters which fully define the optimal joint space motion. The paper presents the impact of different machine learning algorithms for velocity and torque optimal trajectories with respect to optimality and feasibility. To demonstrate the usefulness of the trajectories, a control approach is presented that allows general walking including transitions between points in the task-space

Dynamic Walking: Toward Agile and Efficient Bipedal Robots

Dynamic walking on bipedal robots has evolved from an idea in science fiction to a practical reality. This is due to continued progress in three key areas: a mathematical understanding of locomotion, the computational ability to encode this mathematics through optimization, and the hardware capable of realizing this understanding in practice. In this context, this review article outlines the end-to-end process of methods which have proven effective in the literature for achieving dynamic walking on bipedal robots. We begin by introducing mathematical models of locomotion, from reduced order models that capture essential walking behaviors to hybrid dynamical systems that encode the full order continuous dynamics along with discrete footstrike dynamics. These models form the basis for gait generation via (nonlinear) optimization problems. Finally, models and their generated gaits merge in the context of real-time control, wherein walking behaviors are translated to hardware. The concepts presented are illustrated throughout in simulation, and experimental instantiation on multiple walking platforms are highlighted to demonstrate the ability to realize dynamic walking on bipedal robots that is agile and efficient

Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking

The ability to track a general walking path with specific timing is crucial to the operational safety and reliability of bipedal robots for avoiding dynamic obstacles, such as pedestrians, in complex environments. This paper introduces an online, full-body motion planner that generates the desired impact-aware motion for fully-actuated bipedal robotic walking. The main novelty of the proposed planner lies in its capability of producing desired motions in real-time that respect the discrete impact dynamics and the desired impact timing. To derive the proposed planner, a full-order hybrid dynamic model of fully-actuated bipedal robotic walking is presented, including both continuous dynamics and discrete lading impacts. Next, the proposed impact-aware online motion planner is introduced. Finally, simulation results of a 3-D bipedal robot are provided to confirm the effectiveness of the proposed online impact-aware planner. The online planner is capable of generating full-body motion of one walking step within 0.6 second, which is shorter than a typical bipedal walking step

Motion Planning and Control for the Locomotion of Humanoid Robot

This thesis aims to contribute on the motion planning and control problem of the locomotion of humanoid robots. For the motion planning, various methods were proposed in different levels of model dependence. First, a model free approach was proposed which utilizes linear regression to estimate the relationship between foot placement and moving velocity. The data-based feature makes it quite robust to handle modeling error and external disturbance. As a generic control philosophy, it can be applied to various robots with different gaits. To reduce the risk of collecting experimental data of model-free method, based on the simplified linear inverted pendulum model, the classic planning method of model predictive control was explored to optimize CoM trajectory with predefined foot placements or optimize them two together with respect to the ZMP constraint. Along with elaborately designed re-planning algorithm and sparse discretization of trajectories, it is fast enough to run in real time and robust enough to resist external disturbance. Thereafter, nonlinear models are utilized for motion planning by performing forward simulation iteratively following the multiple shooting method. A walking pattern is predefined to fix most of the degrees of the robot, and only one decision variable, foot placement, is left in one motion plane and therefore able to be solved in milliseconds which is sufficient to run in real time. In order to track the planned trajectories and prevent the robot from falling over, diverse control strategies were proposed according to the types of joint actuators. CoM stabilizer was designed for the robots with position-controlled joints while quasi-static Cartesian impedance control and optimization-based full body torque control were implemented for the robots with torque-controlled joints. Various scenarios were set up to demonstrate the feasibility and robustness of the proposed approaches, like walking on uneven terrain, walking with narrow feet or straight leg, push recovery and so on

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion