Electronics-free pneumatic circuits for controlling soft-legged robots

2021 ◽  
Vol 6 (51) ◽  
pp. eaay2627 ◽  
Author(s):  
Dylan Drotman ◽  
Saurabh Jadhav ◽  
David Sharp ◽  
Christian Chan ◽  
Michael T. Tolley
Keyword(s):  
Degrees Of Freedom ◽  
Low Cost ◽  
Legged Robots ◽  
Walking Robots ◽  
Memory Element ◽  
Walking Gait ◽  
Locomotion Speed ◽  
Control Circuits ◽  
Actuation Systems ◽  
Constant Source

Pneumatically actuated soft robots have recently shown promise for their ability to adapt to their environment. Previously, these robots have been controlled with electromechanical components, such as valves and pumps, that are typically bulky and expensive. Here, we present an approach for controlling the gaits of soft-legged robots using simple pneumatic circuits without any electronic components. This approach produces locomotive gaits using ring oscillators composed of soft valves that generate oscillating signals analogous to biological central pattern generator neural circuits, which are acted upon by pneumatic logic components in response to sensor inputs. Our robot requires only a constant source of pressurized air to power both control and actuation systems. We demonstrate this approach by designing pneumatic control circuits to generate walking gaits for a soft-legged quadruped with three degrees of freedom per leg and to switch between gaits to control the direction of locomotion. In experiments, we controlled a basic walking gait using only three pneumatic memory elements (valves). With two oscillator circuits (seven valves), we were able to improve locomotion speed by 270%. Furthermore, with a pneumatic memory element we designed to mimic a double-pole double-throw switch, we demonstrated a control circuit that allowed the robot to select between gaits for omnidirectional locomotion and to respond to sensor input. This work represents a step toward fully autonomous, electronics-free walking robots for applications including low-cost robotics for entertainment and systems for operation in environments where electronics may not be suitable.

scholarly journals A Quadruped Robot with the Wooden Body for Static Locomotion in a Controlled Environment

2020 ◽  
Author(s):  
Muhammad Bilal Khan
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Position Control ◽  
Low Cost ◽  
Control Design ◽  
Quadruped Robot ◽  
Legged Robots ◽  
Controlled Environment ◽  
Robot Design ◽  
Classroom Setting

We present the design and overall development of an eight degrees of freedom (DOF) based Bioinspired Quadruped Robot (BiQR). The robot is designed with a skeleton made of cedar wood. The wooden skeleton is based on exploring the potential of cedar wood to be a choice for legged robots’ design. With a total weight of 1.19 kg, the robot uses eight servo motors that run the position control. Relying on the inverse kinematics, the control design enables the robot to perform the walk gait-based locomotion in a controlled environment. The robot has two main aspects: 1) the initial wooden skeleton development of the robot showing it to be an acceptable choice for robot design, 2) the robot’s applicability as a low-cost legged platform to test the locomotion in a laboratory or a classroom setting.

scholarly journals Fluid-driven origami-inspired artificial muscles

2017 ◽  
Vol 114 (50) ◽  
pp. 13132-13137 ◽  
Author(s):  
Shuguang Li ◽  
Daniel M. Vogt ◽  
Daniela Rus ◽  
Robert J. Wood
Keyword(s):  
Peak Power ◽  
Degrees Of Freedom ◽  
Multiple Scales ◽  
Low Cost ◽  
Artificial Muscles ◽  
Fluid Medium ◽  
Single Degree Of Freedom ◽  
Flexible Skin ◽  
Actuation Systems ◽  
Power Densities

Artificial muscles hold promise for safe and powerful actuation for myriad common machines and robots. However, the design, fabrication, and implementation of artificial muscles are often limited by their material costs, operating principle, scalability, and single-degree-of-freedom contractile actuation motions. Here we propose an architecture for fluid-driven origami-inspired artificial muscles. This concept requires only a compressible skeleton, a flexible skin, and a fluid medium. A mechanical model is developed to explain the interaction of the three components. A fabrication method is introduced to rapidly manufacture low-cost artificial muscles using various materials and at multiple scales. The artificial muscles can be programed to achieve multiaxial motions including contraction, bending, and torsion. These motions can be aggregated into systems with multiple degrees of freedom, which are able to produce controllable motions at different rates. Our artificial muscles can be driven by fluids at negative pressures (relative to ambient). This feature makes actuation safer than most other fluidic artificial muscles that operate with positive pressures. Experiments reveal that these muscles can contract over 90% of their initial lengths, generate stresses of ∼600 kPa, and produce peak power densities over 2 kW/kg—all equal to, or in excess of, natural muscle. This architecture for artificial muscles opens the door to rapid design and low-cost fabrication of actuation systems for numerous applications at multiple scales, ranging from miniature medical devices to wearable robotic exoskeletons to large deployable structures for space exploration.

scholarly journals A hybrid tactile sensor-based obstacle overcoming method for hexapod walking robots

2020 ◽  
Author(s):  
Mindaugas Luneckas ◽  
Tomas Luneckas ◽  
Dainius Udris ◽  
Darius Plonis ◽  
Rytis Maskeliūnas ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Flat Surface ◽  
Tactile Sensor ◽  
Legged Robots ◽  
Walking Robots ◽  
Positional Error ◽  
Tactile Sensors ◽  
Robot Locomotion ◽  
Promising Solution ◽  
Novel Method

AbstractWalking robots are considered as a promising solution for locomotion across irregular or rough terrain. While wheeled or tracked robots require flat surface like roads or driveways, walking robots can adapt to almost any terrain type. However, overcoming diverse terrain obstacles still remains a challenging task even for multi-legged robots with a high number of degrees of freedom. Here, we present a novel method for obstacle overcoming for walking robots based on the use of tactile sensors and generative recurrent neural network for positional error prediction. By using tactile sensors positioned on the front side of the legs, we demonstrate that a robot is able to successfully overcome obstacles close to robots height in the terrains of different complexity. The proposed method can be used by any type of a legged machine and can be considered as a step toward more advanced walking robot locomotion in unstructured terrain and uncertain environment.

scholarly journals A Quadruped Robot with the Wooden Body for Static Locomotion in a Controlled Environment

2020 ◽  
Author(s):  
Muhammad Bilal Khan ◽  
Ahmad Kamal Khan
Keyword(s):  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Position Control ◽  
Low Cost ◽  
Control Design ◽  
Quadruped Robot ◽  
Legged Robots ◽  
Controlled Environment ◽  
Robot Design ◽  
Classroom Setting

We present the design and overall development of an eight degrees of freedom (DOF) based Bioinspired Quadruped Robot (BiQR). The robot is designed with a skeleton made of cedar wood. The wooden skeleton is based on exploring the potential of cedar wood to be a choice for legged robots’ design. With a total weight of 1.19 kg, the robot uses eight servo motors that run the position control. Relying on the inverse kinematics, the control design enables the robot to perform the walk gait-based locomotion in a controlled environment. The robot has two main aspects: 1) the initial wooden skeleton development of the robot showing it to be an acceptable choice for robot design, 2) the robot’s applicability as a low-cost legged platform to test the locomotion in a laboratory or a classroom setting.

scholarly journals Reconstruction of Relative Phase of Self-Transmitting Devices by Using Multiprobe Solutions and Non-Convex Optimization

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2459
Author(s):  
Rubén Tena Sánchez ◽  
Fernando Rodríguez Varela ◽  
Lars J. Foged ◽  
Manuel Sierra Castañer
Keyword(s):  
Iterative Algorithm ◽  
Degrees Of Freedom ◽  
Relative Phase ◽  
Low Cost ◽  
Initial Guess ◽  
Noise Model ◽  
Medium Size ◽  
Phase Reconstruction ◽  
Linear Combinations ◽  
Iterative Optimization Algorithm

Phase reconstruction is in general a non-trivial problem when it comes to devices where the reference is not accessible. A non-convex iterative optimization algorithm is proposed in this paper in order to reconstruct the phase in reference-less spherical multiprobe measurement systems based on a rotating arch of probes. The algorithm is based on the reconstruction of the phases of self-transmitting devices in multiprobe systems by taking advantage of the on-axis top probe of the arch. One of the limitations of the top probe solution is that when rotating the measurement system arch, the relative phase between probes is lost. This paper proposes a solution to this problem by developing an optimization iterative algorithm that uses partial knowledge of relative phase between probes. The iterative algorithm is based on linear combinations of signals when the relative phase is known. Phase substitution and modal filtering are implemented in order to avoid local minima and make the algorithm converge. Several noise-free examples are presented and the results of the iterative algorithm analyzed. The number of linear combinations used is far below the square of the degrees of freedom of the non-linear problem, which is compensated by a proper initial guess. With respect to noisy measurements, the top probe method will introduce uncertainties for different azimuth and elevation positions of the arch. This is modelled by considering the real noise model of a low-cost receiver and the results demonstrate the good accuracy of the method. Numerical results on antenna measurements are also presented. Due to the numerical complexity of the algorithm, it is limited to electrically small- or medium-size problems.

scholarly journals Task space adaptation via the learning of gait controllers of magnetic soft millirobots

2021 ◽  
pp. 027836492110218
Author(s):  
Sinan O. Demir ◽  
Utku Culha ◽  
Alp C. Karacakol ◽  
Abdon Pena-Francesch ◽  
Sebastian Trimpe ◽  
...  
Keyword(s):  
Human Body ◽  
Degrees Of Freedom ◽  
Bayesian Optimization ◽  
Small Scale ◽  
Soft Robots ◽  
Modeling And Control ◽  
Walking Gait ◽  
Physical Experiments ◽  
Efficient Learning ◽  
Task Environments

Untethered small-scale soft robots have promising applications in minimally invasive surgery, targeted drug delivery, and bioengineering applications as they can directly and non-invasively access confined and hard-to-reach spaces in the human body. For such potential biomedical applications, the adaptivity of the robot control is essential to ensure the continuity of the operations, as task environment conditions show dynamic variations that can alter the robot’s motion and task performance. The applicability of the conventional modeling and control methods is further limited for soft robots at the small-scale owing to their kinematics with virtually infinite degrees of freedom, inherent stochastic variability during fabrication, and changing dynamics during real-world interactions. To address the controller adaptation challenge to dynamically changing task environments, we propose using a probabilistic learning approach for a millimeter-scale magnetic walking soft robot using Bayesian optimization (BO) and Gaussian processes (GPs). Our approach provides a data-efficient learning scheme by finding the gait controller parameters while optimizing the stride length of the walking soft millirobot using a small number of physical experiments. To demonstrate the controller adaptation, we test the walking gait of the robot in task environments with different surface adhesion and roughness, and medium viscosity, which aims to represent the possible conditions for future robotic tasks inside the human body. We further utilize the transfer of the learned GP parameters among different task spaces and robots and compare their efficacy on the improvement of data-efficient controller learning.

An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

2017 ◽  
Vol 44 (4) ◽  
pp. 428-441 ◽  
Author(s):  
Michał R. Nowicki ◽  
Dominik Belter ◽  
Aleksander Kostusiak ◽  
Petr Cížek ◽  
Jan Faigl ◽  
...  
Keyword(s):  
Performance Metrics ◽  
State Of The Art ◽  
Building Blocks ◽  
Bundle Adjustment ◽  
The State ◽  
Legged Robots ◽  
Evaluation Methodology ◽  
Walking Robots ◽  
Content Type ◽  
Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

scholarly journals Soft Spherical Tensegrity Robot Design Using Rod-Centered Actuation and Control

2016 ◽  
Author(s):  
Lee-Huang Chen ◽  
Kyunam Kim ◽  
Ellande Tang ◽  
Kevin Li ◽  
Richard House ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Low Cost ◽  
Space Exploration ◽  
Robot Design ◽  
The Novel ◽  
Flexible Design ◽  
Spherical Robot ◽  
Potential Benefits ◽  
And Performance ◽  
And Control

This paper presents the design, analysis and testing of a fully actuated modular spherical tensegrity robot for co-robotic and space exploration applications. Robots built from tensegrity structures (composed of pure tensile and compression elements) have many potential benefits including high robustness through redundancy, many degrees of freedom in movement and flexible design. However to fully take advantage of these properties a significant fraction of the tensile elements should be active, leading to a potential increase in complexity, messy cable and power routing systems and increased design difficulty. Here we describe an elegant solution to a fully actuated tensegrity robot: The TT-3 (version 3) tensegrity robot, developed at UC Berkeley, in collaboration with NASA Ames, is a lightweight, low cost, modular, and rapidly prototyped spherical tensegrity robot. This robot is based on a ball-shaped six-bar tensegrity structure and features a unique modular rod-centered distributed actuation and control architecture. This paper presents the novel mechanism design, architecture and simulations of TT-3, the first untethered, fully actuated cable-driven six-bar tensegrity spherical robot ever built and tested for mobility. Furthermore, this paper discusses the controls and preliminary testing performed to observe the system’s behavior and performance.

Low-cost Indirect Measurement Methods for Self-x Integrated Sensory Electronics for Industry 4.0

2020 ◽  
Vol 87 (s1) ◽  
pp. s79-s84
Author(s):  
Qummar Zaman ◽  
Senan Alraho ◽  
Andreas König
Keyword(s):  
Industry 4.0 ◽  
Degrees Of Freedom ◽  
Performance Metrics ◽  
Low Cost ◽  
Indirect Measurement ◽  
Measurement Methods ◽  
Instrumentation Amplifier ◽  
Performance Parameters ◽  
Current Feedback ◽  
Indirect Measurements

AbstractThe conventional method for testing the performance of reconfigurable sensory electronics of industry 4.0 relies on the direct measurement methods. This approach gives higher accuracy but at the price of extremely high testing cost and does not utilize the new degrees of freedom for measurement methods enabled by industry 4.0. In order to reduce the test cost and use available resources more efficiently, a primary approach, called indirect measurements or alternative testing has been proposed using a non-intrusive sensor. Its basic principle consists in using the indirect measurements, in order to estimate the sensory electronics performance parameters without measuring directly. The non-intrusive property of the proposed method offers better performance of the sensing electronics and virtually applicable to any sensing electronics. Efficiency is evaluated in terms of model accuracy by using six different classical metrics. It uses an indirect current-feedback instrumentation amplifier (InAmp) as a test vehicle to evaluate the performance parameters of the circuit. The device is implemented using CMOS 0.35 μm technology. The achieved maximum value of average expected error metrics is 0.24, and the lowest value of correlation performance metrics is 0.91, which represent an excellent efficiency of InAmp performance predictor.

Feasibility Study of Designing a Three Legged Walking Robot: Tribot

1991 ◽  
Author(s):  
Yueh-Jaw Lin ◽  
Aaron Tegland
Keyword(s):  
Feasibility Study ◽  
Legged Robots ◽  
Walking Robots ◽  
Design Parameters ◽  
Optimized Design ◽  
Motion Simulation ◽  
Walking Robot ◽  
Design Considerations ◽  
Simulation Based ◽  
Weight Distributions

Abstract In recent years, walking robot research has become an important robotic research topic because walking robots possess mobility, as oppose to stationary robots. However, current walking robot research has only concentrated on even numbered legged robots. Walking robots with odd numbered legs are still lack of attention. This paper presents the study on an odd numbered legged (three-legged) walking robot — Tribot. The feasibility of three-legged walking is first investigated using computer simulation based on a scaled down tribot model. The computer display of motion simulation shows that a walking robot with three legs is feasible with a periodic gait. During the course of the feasibility study, the general design of the three-legged robot is also analyzed for various weights, weight distributions, and link lengths. In addition, the optimized design parameters and limitations are found for certain knee arrangements. These design considerations and feasibility study using computer display can serve as a general guideline for designing odd numbered legged robots.

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