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

Xie, Li; Henkel, Christian; Stol, Karl; Wang, Xu

doi:10.1177/1729881418754563

Cited by 36 publications

(31 citation statements)

References 19 publications

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“…Many research works have achieved the goal of saving energy through trajectory optimization [20][21][22]. Xie.…”

Section: Of 15mentioning

confidence: 99%

“…Their results showed that following the same straight-line path via different velocity profiles consumed different amounts of energy. However, their studies were restricted to straight-line paths and stationary states in the beginning and at the end, and hence became less practical for autonomous navigation [21]. Bartlett et al proposed a probabilistic, data-driven approach to estimating the energy consumption of a mobile robot on a set of trajectories, whether they have been traversed or not.…”

Section: Of 15mentioning

confidence: 99%

“…The energy consumption of the control system depends on the power of the control circuit boards [21], which is related to the running state of the robot. The energy modeling of the control system is mainly divided into the following three parts: the energy consumption in the standby state, the energy consumption when the robot just starts to move, and the energy consumption when the robot runs smoothly.…”

Section: Energy Consumption Of the Control Systemmentioning

confidence: 99%

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Energy Modeling and Power Measurement for Mobile Robots

2018

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To improve the energy efficiency of a mobile robot, a novel energy modeling method for mobile robots is proposed in this paper. The robot can calculate and predict energy consumption through the energy model, which provides a guide to facilitate energy-efficient strategies. The energy consumption of the mobile robot is first modeled by considering three major factors: the sensor system, control system, and motion system. The relationship between the three systems is elaborated by formulas. Then, the model is utilized and experimentally tested in a four-wheeled Mecanum mobile robot. Furthermore, the power measurement methods are discussed. The energy consumption of the sensor system and control system was at the milliwatt level, and a Monsoon power monitor was used to accurately measure the electrical power of the systems. The experimental results showed that the proposed energy model can be used to predict the energy consumption of the robot movement processes in addition to being able to efficiently support the analysis of the energy consumption characteristics of mobile robots.

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“…Many research works have achieved the goal of saving energy through trajectory optimization [20][21][22]. Xie.…”

Section: Of 15mentioning

confidence: 99%

Section: Of 15mentioning

confidence: 99%

Section: Energy Consumption Of the Control Systemmentioning

confidence: 99%

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Energy Modeling and Power Measurement for Mobile Robots

2018

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“…So, the energy consumption of MRs comes from four subsystems of MR: Motion system, control system, sensor system, and communication system, as shown in Figure 2. After the energy model of MR is formulated [18][19][20], the power consumption of the four robotic subsystems can be calculated by the power consumption model. By establishing the relationship between the power consumption of each subsystem, the optimal algorithm to reduce the energy consumption of the robot can be obtained [14].…”

Section: Introductionmentioning

confidence: 99%

Energy Modeling and Power Measurement for Three-Wheeled Omnidirectional Mobile Robots for Path Planning

2019

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Due to their high mobility, mobile robots (MR) are widely used in intelligent manufacturing. Due to the perfect symmetry of the MR of the three-wheeled moving chassis, it can move quickly in a crowded and complex factory environment. Because it is powered by a lithium battery, in order to improve its energy efficiency, we need to ensure that its power consumption is reduced as much as possible in order to avoid frequent battery replacement. The power consumption of MRs has also become an important research focus for researchers. Therefore, a power consumption modeling of the omnidirectional mobility of the three-wheeled omnidirectional mobile robot (TOMR) is proposed in this paper. When TOMR advances heading at different angles, the speed of each wheel changes dramatically. So, the power consumption of robots will also be greatly changed. In this paper, the energy and power consumption of the robot heading in different directions is analyzed and modeled by formulas. This research can be valuable for path planning and control design. Omnidirectional wheel (a) (b) Figure 1. Three-wheeled omnidirectional mobile robot (TOMR). (a) Schematic of TOMR and a (b) schematic diagram of robot architecture.

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“…It is of great significance to study the energy consumption of the mobile robots, and energy-saving strategies have been conducted by many researchers via different aspects, for example, trajectory planning [4][5][6], motion control [7,8], and mechanical design [9]. In order to study the energy-efficient strategies, a detailed and accurate energy consumption model needs to first be established for the robot system.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Torque Distribution Optimization for an Omnidirectional Mobile Robot with Powered Caster Wheels

et al. 2019

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A mobile robot with no less than two powered caster wheels (PCWs) has the ability to perform omnidirectional motions and belongs to a redundantly actuated system. Redundant actuation will bring the issue of non-uniqueness of actuating torque distribution, and inappropriate choices of torque distribution schemes will lead to unexpected large required actuating torques and extra energy consumption. This paper proposes a new torque distribution optimization approach based on a gradient projection method (GPM) for the omnidirectional mobile robot (OMR) with direct drive PCWs. It can significantly reduce the maximal required actuating torque and the energy consumption of the system. The modular kinematic and dynamic modeling method is presented first, which is suitable for an arbitrary number of employed PCWs, as well as their install positions in the chassis. The detailed energy consumption model of the OMR, including output energy consumption and electrical energy loss, is formulated through experimental testing. The effectiveness of the proposed algorithms is validated by simulation examples. Lastly, the computational efficiency of the method is verified. components: the sensor system, control system, and motion system. It is clarified by experiments that the motion system part consumes the overwhelming majority of energy, with up to more than 90%. Xu et al. [11] present an energy consumption modelling method for an industry robot. Their method does not have to measure the relevant parameters inside the robot and mainly concerns torque modelling. A parameter estimation method is proposed for the torque modelling. Verstraten et al. [12] study several modeling methods that are commonly adopted. They investigate how well these methods can be used to describe the energy consumption of a DC motor while performing dynamic tasks. The conclusion resulted from their work provides guidelines in determining which factors should be included in the energy consumption model. In this paper, we aim to study the impacts of different torque distribution schemes on the energy consumption of the OMR with PCWs. Hence, we focus on formulating the energy consumption model based on the actuation torques. Besides theoretical energy consumption modelling, the accurate experimental measurement of energy consumption is necessary for the evaluation of energy consumption of a system combined with hardware and software. Laopoulos et al.[13] present a current measurement method that monitors the instantaneous supply current. The method can provide high-performance evaluation of energy consumption, especially for low-power applications. Roennau et al. [14] propose an energy consumption estimation based on an on-board current measurement for each joint individually and employ a non-linear function to fit the measurement. There are two different motors integrated in a single PCW, which are responsible for rolling and steering motions, respectively. The energy consumption modelling methods for the two motors are unified; detailed specifications of t...

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

Cited by 36 publications

References 19 publications

Energy Modeling and Power Measurement for Mobile Robots

Energy Modeling and Power Measurement for Mobile Robots

Energy Modeling and Power Measurement for Three-Wheeled Omnidirectional Mobile Robots for Path Planning

Energy-Efficient Torque Distribution Optimization for an Omnidirectional Mobile Robot with Powered Caster Wheels

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