scholarly journals Power-minimization and energy-reduction autonomous navigation of an omnidirectional Mecanum robot via the dynamic window approach local trajectory planning

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141875456 ◽  
Author(s):  
Li Xie ◽  
Christian Henkel ◽  
Karl Stol ◽  
Weiliang Xu
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Trajectory Planning ◽  
Autonomous Navigation ◽  
High Speed ◽  
Energy Reduction ◽  
New Energy ◽  
Mecanum Wheel ◽  
Major Factors ◽  
Window Approach

To improve the energy efficiency of the Mecanum wheel, this article extends the dynamic window approach by adding a new energy-related criterion for minimizing the power consumption of autonomous mobile robots. The energy consumption of the Mecanum robot is first modeled by considering major factors. Then, the model is utilized in the extended dynamic window approach–based local trajectory planner to additionally evaluate the omnidirectional velocities of the robot. Based on the new trajectory planning objective that minimizes power consumption, energy-reduction autonomous navigation is proposed via the combinational cost objectives of low power consumption and high speed. Comprehensive experiments are performed in various autonomous navigation task scenarios, to validate the energy consumption model and to show the effectiveness of the proposed technique in minimizing the power consumption and reducing the energy consumption. It is observed that the technique effectively takes advantage of the Mecanum robot’s redundant maneuverability, can cope with any type of path and is able to fulfil online obstacle avoidance.

scholarly journals Practical Model for Energy Consumption Analysis of Omnidirectional Mobile Robot

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Load Capacity ◽  
Working Environment ◽  
Energy Consumption Analysis ◽  
Mecanum Wheel ◽  
Save Energy ◽  
Energy Consumption Modeling ◽  
Robot Platform

The four-wheeled Mecanum robot is widely used in various industries due to its maneuverability and strong load capacity, which is suitable for performing precise transportation tasks in a narrow environment. While the Mecanum wheel robot has mobility, it also consumes more energy than ordinary robots. The power consumed by the Mecanum wheel mobile robot varies enormously depending on their operating regimes and environments. Therefore, only knowing the working environment of the robot and the accurate power consumption model can we accurately predict the power consumption of the robot. In order to increase the applicable scenarios of energy consumption modeling for Mecanum wheel robots and improve the accuracy of energy consumption modeling, this paper focuses on various factors that affect the energy consumption of the Mecanum wheel robot, such as motor temperature, terrain, the center of gravity position, etc. The model is derived from the kinematic and kinetic model combined with electrical engineering and energy flow principles. The model has been simulated in MATLAB and experimentally validated with the four-wheeled Mecanum robot platform in our lab. Experimental results show that the accuracy of the model reached 95%. The results of energy consumption modeling can help robots save energy by helping them to perform rational path planning and task planning.

scholarly journals Navigation of Autonomous Light Vehicles Using an Optimal Trajectory Planning Algorithm

2021 ◽  
Vol 13 (3) ◽  
pp. 1233
Author(s):  
Ángel Valera ◽  
Francisco Valero ◽  
Marina Vallés ◽  
Antonio Besa ◽  
Vicente Mata ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Trajectory Planning ◽  
Autonomous Navigation ◽  
Optimal Trajectory ◽  
Computational Cost ◽  
Initial Point ◽  
Target Point ◽  
Software Components ◽  
Planning Algorithm ◽  
Optimal Trajectory Planning

Autonomous navigation is a complex problem that involves different tasks, such as location of the mobile robot in the scenario, robotic mapping, generating the trajectory, navigating from the initial point to the target point, detecting objects it may encounter in its path, etc. This paper presents a new optimal trajectory planning algorithm that allows the assessment of the energy efficiency of autonomous light vehicles. To the best of our knowledge, this is the first time in the literature that this is carried out by minimizing the travel time while considering the vehicle’s dynamic behavior, its limitations, and with the capability of avoiding obstacles and constraining energy consumption. This enables the automotive industry to design environmentally sustainable strategies towards compliance with governmental greenhouse gas (GHG) emission regulations and for climate change mitigation and adaptation policies. The reduction in energy consumption also allows companies to stay competitive in the marketplace. The vehicle navigation control is efficiently implemented through a middleware of component-based software development (CBSD) based on a Robot Operating System (ROS) package. It boosts the reuse of software components and the development of systems from other existing systems. Therefore, it allows the avoidance of complex control software architectures to integrate the different hardware and software components. The global maps are created by scanning the environment with FARO 3D and 2D SICK laser sensors. The proposed algorithm presents a low computational cost and has been implemented as a new module of distributed architecture. It has been integrated into the ROS package to achieve real time autonomous navigation of the vehicle. The methodology has been successfully validated in real indoor experiments using a light vehicle under different scenarios entailing several obstacle locations and dynamic parameters.

scholarly journals A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks

2020 ◽  
Vol 12 (6) ◽  
pp. 1381-1401 ◽  
Author(s):  
Yassine Himeur ◽  
Abdullah Alsalemi ◽  
Faycal Bensaali ◽  
Abbes Amira
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Network Architecture ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Climate Conditions ◽  
System A ◽  
Novel Approach ◽  
New Energy ◽  
Moment Features

AbstractNowadays, analyzing, detecting, and visualizing abnormal power consumption behavior of householders are among the principal challenges in identifying ways to reduce power consumption. This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model. The latter is used to draw out load characteristics using daily intent-driven moments of user consumption actions. Besides micro-moment features extraction, we also experiment with a deep neural network architecture for efficient abnormality detection and classification. In the following, a novel anomaly visualization technique is introduced that is based on a scatter representation of the micro-moment classes, and hence providing consumers an easy solution to understand their abnormal behavior. Moreover, in order to validate the proposed system, a new energy consumption dataset at appliance level is also designed through a measurement campaign carried out at Qatar University Energy Lab, namely, Qatar University dataset. Experimental results on simulated and real datasets collected at two regions, which have extremely different climate conditions, confirm that the proposed deep micro-moment architecture outperforms other machine learning algorithms and can effectively detect anomalous patterns. For example, 99.58% accuracy and 97.85% F1 score have been achieved under Qatar University dataset. These promising results establish the efficacy of the proposed deep micro-moment solution for detecting abnormal energy consumption, promoting energy efficiency behaviors, and reducing wasted energy.

Performance simulation and energetic analysis of TBot high-speed cable-driven parallel robot

2021 ◽  
pp. 1-14
Author(s):  
Jinhao Duan ◽  
Zhufeng Shao ◽  
Zhaokun Zhang ◽  
Fazhong Peng
Keyword(s):  
Energy Consumption ◽  
Trajectory Planning ◽  
High Speed ◽  
Low Cost ◽  
Parallel Robot ◽  
Industrial Applications ◽  
Parallel Robots ◽  
Dynamics Modeling ◽  
Serial Robots ◽  
Key Issues

Abstract Compared with serial robots, parallel robots have the advantages of high stiffness and good dynamics. By replacing the rigid limbs with cables, the cable-driven parallel robot (CDPR) is greatly simplified in structure and lightweight. We designed a high-speed CDPR tensioned by the passive rod and spring, named TBot. The robot can realize the SCARA movement as the classical Delta parallel robot. Comparison analysis of TBot and Delta is carried out to reveal the natures of the CDPRs and rigid parallel robots, identify the key issues, and promote industrial applications. Based on kinematics and dynamics modeling, performances are analyzed with simulation under a typical Adept Motion trajectory. Results illustrate that TBot has advantages of low cost, low inertia, low energy consumption and adjustable workspace and has great application potential. Energy consumption of the TBot is discussed and the trajectory planning is studied with the genetic algorithm to further reduce the energy consumption, considering the influence of the passive spring. Finally, on the basis of 30% less energy consumption for the Adept Motion than Delta, extra 14.3% energy consumption is saved through the trajectory planning of TBot.

Reducing energy consumption via trajectory planning method for delta high-speed parallel manipulator

2019 ◽  
pp. 002072091989420
Author(s):  
Cheng Liu ◽  
Guohua Cao ◽  
Yongyin Qu
Keyword(s):  
Energy Consumption ◽  
Obstacle Avoidance ◽  
Trajectory Planning ◽  
High Speed ◽  
Polynomial Interpolation ◽  
Parallel Robot ◽  
Joint Space ◽  
Degree Polynomial ◽  
Operating Space ◽  
Motion Characteristics

This paper selects delta high-speed parallel robot with three degrees of freedom as the research object. The trajectory planning strategies of Cartesian space and angular displacement, angular velocity and angular acceleration of three joints in high-speed handling are studied. Firstly, the critical trajectory points starting point and end point, and points for obstacle avoidance height are set up, and then according to the inverse kinematics model of the robot, a point-to-point “door” type moving trajectory is established, and the mapping relationship between the motion characteristics of the operating space and the motion characteristics of the joint space is established by using the 4-3-4 degree polynomial motion law in the operating space. However, aiming at the higher energy consumption of 4-3-4 degree polynomial interpolation caused by longer the trajectory, and difficult control of obstacle avoidance height, one key point is added. Thereby, the motion rules are interpolated by 4-3-3-4 degree polynomial interpolation, and the mapping relationship between the motion characteristics of the operating space and the motion characteristics of the joint space is established. Two trajectory planning methods are simultaneously simulated under the same keys points and the same trajectory time range. The motion characteristics of the joint rotation angle of the parallel robot between polynomial interpolations are respectively compared. The results show that the trajectory planning method based on 4-3-3-4 degree polynomial interpolation in joint space has obvious advantages in improving the running state of the delta parallel robot and reducing the energy consumption of the system.

Design and Implementation of an Efficient Parallel LFSR Architecture for Wireless Communication Systems

2019 ◽  
Vol 14 ◽  
Author(s):  
A. Suresh Babu ◽  
B. Anand
Keyword(s):  
Wireless Communication ◽  
Power Consumption ◽  
Low Power ◽  
Communication Systems ◽  
High Speed ◽  
Design Tool ◽  
Shift Register ◽  
Linear Feedback ◽  
Wireless Communication Systems ◽  
Coverage Area

: A Linear Feedback Shift Register (LFSR) considers a linear function typically an XOR operation of the previous state as an input to the current state. This paper describes in detail the recent Wireless Communication Systems (WCS) and techniques related to LFSR. Cryptographic methods and reconfigurable computing are two different applications used in the proposed shift register with improved speed and decreased power consumption. Comparing with the existing individual applications, the proposed shift register obtained >15 to <=45% of decreased power consumption with 30% of reduced coverage area. Hence this proposed low power high speed LFSR design suits for various low power high speed applications, for example wireless communication. The entire design architecture is simulated and verified in VHDL language. To synthesis a standard cell library of 0.7um CMOS is used. A custom design tool has been developed for measuring the power. From the results, it is obtained that the cryptographic efficiency is improved regarding time and complexity comparing with the existing algorithms. Hence, the proposed LFSR architecture can be used for any wireless applications due to parallel processing, multiple access and cryptographic methods.

A Split Network based Routing Approach in Wireless Sensor Network to Enhance Network Stability

2019 ◽  
Vol 9 (4) ◽  
pp. 480-487 ◽  
Author(s):  
Hardeep S. Saini ◽  
Dinesh Arora
Keyword(s):  
Energy Consumption ◽  
Sensor Network ◽  
Energy Efficient ◽  
Cluster Head ◽  
Base Station ◽  
Operating Efficiency ◽  
Network Stability ◽  
Major Factors ◽  
Ch Selection

Background & Objective: The operating efficiency of a sensor network totally relies upon the energy that is consumed by the nodes to perform various tasks like data transmission etc. Thus, it becomes mandatory to consume the energy in an intelligent way so that the network can run for a long period. This paper proposed an energy efficient Cluster Head (CH) selection mechanism by considering the distance to Base Station (BS), distance to node and energy as major factors. The concept of volunteer node is also introduced with an objective to reduce the energy consumption of the CH to transmit data from source to BS. The role of the volunteer node is to transmit the data successfully from source to destination or BS. Conclusion: The results are observed with respect to the Alive nodes, dead nodes and energy consumption of the network. The outcome of the proposed work proves that it outperforms the traditional mechanisms.

Low Power and High Speed Sequential Circuits Test Architecture

2019 ◽  
Vol 12 ◽  
Author(s):  
Ahmed K. Jameil ◽  
Yasir Amer Abbas ◽  
Saad Al-Azawi
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Test Generation ◽  
High Speed ◽  
Fir Filter ◽  
Sequential Circuits ◽  
Fir Filters ◽  
Design Verification ◽  
Sequential Circuit ◽  
Generation Algorithm

Background: The designed circuits are tested for faults detection in fabrication to determine which devices are defective. The design verification is performed to ensure that the circuit performs the required functions after manufacturing. Design verification is regarded as a test form in both sequential and combinational circuits. The analysis of sequential circuits test is more difficult than in the combinational circuit test. However, algorithms can be used to test any type of sequential circuit regardless of its composition. An important sequential circuit is the finite impulse response (FIR) filters that are widely used in digital signal processing applications. Objective: This paper presented a new design under test (DUT) algorithm for 4-and 8-tap FIR filters. Also, the FIR filter and the proposed DUT algorithm is implemented using field programmable gate arrays (FPGA). Method: The proposed test generation algorithm is implemented in VHDL using Xilinx ISE V14.5 design suite and verified by simulation. The test generation algorithm used FIR filtering redundant faults to obtain a set of target faults for DUT. The fault simulation is used in DUT to assess the benefit of test pattern in fault coverage. Results: The proposed technique provides average reductions of 20 % and 38.8 % in time delay with 57.39 % and 75 % reductions in power consumption and 28.89 % and 28.89 % slices reductions for 4- and 8-tap FIR filter, respectively compared to similar techniques. Conclusions: The results of implementation proved that a high speed and low power consumption design can be achieved. Further, the speed of the proposed architecture is faster than that of existing techniques.

scholarly journals Ultracompact and low-power-consumption silicon thermo-optic switch for high-speed data

Nanophotonics ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 937-945
Author(s):  
Ruihuan Zhang ◽  
Yu He ◽  
Yong Zhang ◽  
Shaohua An ◽  
Qingming Zhu ◽  
...  
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
High Speed ◽  
High Performance ◽  
Pulse Amplitude ◽  
Telecommunication Networks ◽  
Low Power Consumption ◽  
Power Efficient ◽  
High Speed Data ◽  
On Chip

AbstractUltracompact and low-power-consumption optical switches are desired for high-performance telecommunication networks and data centers. Here, we demonstrate an on-chip power-efficient 2 × 2 thermo-optic switch unit by using a suspended photonic crystal nanobeam structure. A submilliwatt switching power of 0.15 mW is obtained with a tuning efficiency of 7.71 nm/mW in a compact footprint of 60 μm × 16 μm. The bandwidth of the switch is properly designed for a four-level pulse amplitude modulation signal with a 124 Gb/s raw data rate. To the best of our knowledge, the proposed switch is the most power-efficient resonator-based thermo-optic switch unit with the highest tuning efficiency and data ever reported.

scholarly journals A novel navigation system for an autonomous mobile robot in an uncertain environment

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Meng-Yuan Chen ◽  
Yong-Jian Wu ◽  
Hongmei He
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Clustering Algorithm ◽  
Modular Design ◽  
Optimal Path ◽  
Surrounding Environment ◽  
Computing Complexity ◽  
The Arts ◽  
Window Approach

Abstract In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.

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