Exploration of Turning Strategies for an Unconventional Non-Anthropomorphic Bipedal Robot

2017 ◽  
Author(s):  
Jeffrey Yu ◽  
Joshua Hooks ◽  
Sepehr Ghassemi ◽  
Dennis Hong
Keyword(s):  
Sagittal Plane ◽  
Robotic System ◽  
Reaction Wheel ◽  
Bipedal Robot ◽  
Pivot Point

This paper presents our findings in exploring various approaches for turning on a novel prototype biped which takes inspiration from humanoids, but features fundamental differences that increase its stability while reducing its cost and complexity. This non-anthropomorphic robotic system modifies the traditional humanoid form by aligning the legs in the sagittal plane and adding a compliant element to the feet. As this approach to locomotion is relatively new, turning methods have yet to be explored. Turning on this unique platform is a nontrivial problem that we examined by adding additional DoF in the forms of arms or hip actuators. The turning strategies tested include using the hand or foot as a pivot point, utilizing the arms like a tail or reaction wheel, and adding another DoF to each leg. The methods were tested quantitatively to assess their rotational accuracy and qualitatively to evaluate their viability in certain situations.

Liquid State Machine to Generate the Movement Profiles for the Gait Cycle of a 6 DOF Bipedal Robot in a Sagittal Plane

2018 ◽  
Author(s):  
Jesús Franco-Robles ◽  
Alejandro De Lucio-Rangel ◽  
Karla A. Camarillo-Gómez ◽  
Gerardo I. Pérez-Soto ◽  
Jesús Rivera-Guillén
Keyword(s):  
Time Series ◽  
Multilayer Perceptron ◽  
Liquid State ◽  
Gait Cycle ◽  
Sagittal Plane ◽  
Experimental Result ◽  
Forward Kinematics ◽  
Neuronal System ◽  
Bipedal Robot ◽  
Input Time

In this paper, a neuronal system with the ability to generate motion profiles and profiles of the ZMP in a 6DoF bipedal robot in the sagittal plane, is presented. The input time series for LSM training are movement profiles of the oscillating foot trajectory obtained by forward kinematics performed by a previously trained ANN multilayer perceptron. The profiles of objective movement for training are acquired from the analysis of the human walk. Based on a previous simulation of the bipedal robot, a profile of the objective ZMP will be generated for the y–axis and another for the z–axis to know its behavior during the training walk. As an experimental result, the LSM generates new motion profiles and ZMP, given a different trajectory with which it was trained. With the LSM it will be possible to propose new trajectories of the oscillating foot, where it will be known if this trajectory will be stable, by the ZMP, and what movement profile for each articulation will be required to reach this trajectory.

Dynamic locomotion synchronization of bipedal robot and human operator via bilateral feedback teleoperation

2019 ◽  
Vol 4 (35) ◽  
pp. eaav4282 ◽  
Author(s):  
Joao Ramos ◽  
Sangbae Kim
Keyword(s):  
Sagittal Plane ◽  
Frontal Plane ◽  
Humanoid Robots ◽  
Human Locomotion ◽  
Human Motion ◽  
Body Motion ◽  
Human Operator ◽  
Whole Body ◽  
Physical Endurance ◽  
Bipedal Robot

Despite remarkable progress in artificial intelligence, autonomous humanoid robots are still far from matching human-level manipulation and locomotion proficiency in real applications. Proficient robots would be ideal first responders to dangerous scenarios such as natural or man-made disasters. When handling these situations, robots must be capable of navigating highly unstructured terrain and dexterously interacting with objects designed for human workers. To create humanoid machines with human-level motor skills, in this work, we use whole-body teleoperation to leverage human control intelligence to command the locomotion of a bipedal robot. The challenge of this strategy lies in properly mapping human body motion to the machine while simultaneously informing the operator how closely the robot is reproducing the movement. Therefore, we propose a solution for this bilateral feedback policy to control a bipedal robot to take steps, jump, and walk in synchrony with a human operator. Such dynamic synchronization was achieved by (i) scaling the core components of human locomotion data to robot proportions in real time and (ii) applying feedback forces to the operator that are proportional to the relative velocity between human and robot. Human motion was sped up to match a faster robot, or drag was generated to synchronize the operator with a slower robot. Here, we focused on the frontal plane dynamics and stabilized the robot in the sagittal plane using an external gantry. These results represent a fundamental solution to seamlessly combine human innate motor control proficiency with the physical endurance and strength of humanoid robots.

Standing Posture Control of Bipedal Robots with Adaptive Compliance Under Unknown Payload Variations and External Disturbances

2017 ◽  
Vol 14 (03) ◽  
pp. 1750014
Author(s):  
Yichao Mao ◽  
Qiuguo Zhu ◽  
Chunlin Zhou ◽  
Rong Xiong
Keyword(s):  
Sagittal Plane ◽  
Adaptive Controller ◽  
Bipedal Robots ◽  
External Disturbances ◽  
Bipedal Robot ◽  
Static State ◽  
Load Variations ◽  
Optimal Estimator ◽  
Model Control ◽  
Support Phase

When executing tasks, robots are required to demonstrate compliance to unexpected external disturbances or human–robot interactions, and return to the demanded posture when the disturbances or contacts are removed. Traditional Virtual Model Control (VMC) requires precise gravitational compensation to accurately control the posture of a robot. Hence, load variations or other uncertain unmodeled factors in the robot will result in offsets to its balance posture, which makes the robot deviate from the demanded posture when it is in a static state. To reject this offset without sacrificing the compliance of the robot, an adaptive controller is proposed in this paper to implement adaptive compliance on the robot, which makes the robot robust to the variations in gravitational loads in the double leg support phase. The adaptive controller is a combination of the VMC controller and an online gravitational loads estimator, in which the estimator is derived in the double leg support phase to estimate the values of these parameters and obtains an online updating law based on a Kalman optimal estimator. Then, a Lyapunov function is designed to modify and combine the controller and the online gravitational loads estimator. The experiments are conducted on a 4 DoF bipedal robot in the sagittal plane to validate the effectiveness of the controller and show that, by estimating the gravitational loads of the robot, the effects of load variations on balance posture are rejected without sacrificing compliance.

Design and Control of the Planar Bipedal Robot ERNIE

2007 ◽  
Author(s):  
T. Yang ◽  
E. R. Westervelt ◽  
J. P. Schmiedeler ◽  
R. A. Bockbrader
Keyword(s):  
Sagittal Plane ◽  
Control Strategies ◽  
Frontal Plane ◽  
High Gain ◽  
Bipedal Walking ◽  
Knee Joints ◽  
Confined Space ◽  
Bipedal Robot ◽  
Hybrid Zero Dynamics ◽  
And Control

This paper presents the development of the planar bipedal robot ERNIE. ERNIE has 5 links: a torso, two femurs and two tibias without feet. ERNIE was designed and constructed to serve as a testbed for the development of novel control strategies for bipedal walking. A boom provides frontal plane stability, restricting walking motions to the sagittal plane, and ERNIE is configured to walk on a treadmill so that it can walk indefinitely in a confined space. ERNIE’s legs are modular so that morphological asymmetries and the use of feet may be explored more in future studies. Springs can be attached across the knee joints in parallel with the knee actuators to enable gaits that are more energetically efficient. ERNIE is currently controlled using the hybrid zero dynamics framework in which a function of the robot’s configuration that monotonically increases over a step is used to parameterize holonomic constraints on the robot’s motion. The constraints are designed via parameter optimization to minimize an objective function, such as the energy consumed over a step, and, at the same time, ensure gait stability. The constraints are enforced using decoupled high-gain PD control.

Liquid State Machine to Generate the Movement Profiles for the Gait Cycle of a Six Degrees-of-Freedom Bipedal Robot in a Sagittal Plane

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Jesús Franco-Robles ◽  
Alejandro De Lucio-Rangel ◽  
Karla A. Camarillo-Gómez ◽  
Gerardo I. Pérez-Soto ◽  
Miguel A. Martínez-Prado
Keyword(s):  
Time Series ◽  
Liquid State ◽  
Degrees Of Freedom ◽  
Gait Cycle ◽  
Sagittal Plane ◽  
State Machine ◽  
Supervised Machine Learning ◽  
Human Gait ◽  
Bipedal Robot ◽  
Six Degrees Of Freedom

Abstract In this paper, an approach based on a liquid state machine (LSM) to compute the movement profiles to achieve a gait pattern subject to different variations in its trajectory is presented. At the same time, the position of the zero moment point (ZMP) to determine the stability of the six degrees-of-freedom (6DOF) bipedal robot in the sagittal plane during the gait cycle is calculated. The system is constructed as a supervised machine learning model. The time series of the oscillating foot trajectory obtained by direct kinematics with a multilayer perceptron neural network (MLP), to strengthen the kinematic model, is considered as input values for training. The target movement profiles are acquired of a human gait cycle analysis in three different scenarios: normal gait, climbing stairs, and descending stairs. In training, this model also gets the trajectories of the ZMP position during the gait cycle, as target time series. The LSM formed by spiking neurons, considered as third-generation neural networks, is compared in the accuracy of prediction, by the dynamic time warping (DTW) technique and correlation analysis, against the human gait analysis database. With this neuronal system, the joint positions to generate a trajectory of the oscillating foot and the ZMP position of the bipedal in the sagittal plane in different scenarios are obtained, proving the robustness of the LSM.

Frontal plane algorithms for dynamic bipedal walking

Robotica ◽  
2004 ◽  
Vol 22 (1) ◽  
pp. 29-39 ◽  
Author(s):  
Chee-Meng Chew ◽  
Gill A. Pratt
Keyword(s):  
Reinforcement Learning ◽  
Sagittal Plane ◽  
Learning Algorithm ◽  
Frontal Plane ◽  
The Other ◽  
Bipedal Walking ◽  
Control Law ◽  
Bipedal Robot ◽  
Foot Placement ◽  
Simulation Results

This paper presents two frontal plane algorithms for 3D dynamic bipedal walking. One of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. The algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3D bipedal robot to achieve level ground walking. The simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.

Secondary Fractures Following Internal Fixation in Two Horses

1989 ◽  
Vol 02 (03) ◽  
pp. 125-128
Author(s):  
E. M. Gaughan ◽  
N. G. Duchar
Keyword(s):  
Internal Fixation ◽  
Sagittal Plane ◽  
Proximal Phalanx ◽  
Fracture Repair ◽  
Fracture Line ◽  
Carpal Bone ◽  
Fracture Plane ◽  
The Third ◽  
Lag Screw ◽  
Secondary Fractures

SummaryImplant associated fractures have not been reported in horses. Two horses were evaluated for fractures in the fore limbs, occurring subsequent to previous fracture repair. Previously, the horses had sustained fractures of unusual configurations which were repaired using internal fixation. Following repair and healing of the fractures, secondary fractures occurred in the same bone, but in a different (more common) configuration. The first horse was evaluated ten months following lag screw fixation of a longitudinal fracture of the proximal phalanx in a frontal plane. This horse presented with a more typical comminuted fracture in the sagittal plane with the screws from the first fixation lying in the fracture line. This fracture was successfully treated with a cast. The second horse was examined eightteen months after repair of a medial sagittal slab fracture of the third carpal bone. The horse presented with a more typical dorsal slab fracture of the third carpal bone with the previously placed lag screw lying in the fracture line. The screw was removed and a lag screw was placed perpendicular to the new fracture plane through the dorsal surface of the third carpal bone to repair the fracture.

Microsurgery Robotic System for the Deep Complicated Procedures: Progress and Future

Skull Base ◽  
2007 ◽  
Vol 17 (S 1) ◽  
Author(s):  
Akio Morita ◽  
Ryo Mochizuki ◽  
Mamoru Mitsuishi ◽  
Shigeo Sora
Keyword(s):  
Robotic System
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