Energy-based path planning for skid-steer vehicles operating in areas with mixed surface types

Pentzer, Jesse; Reichard, Karl; Brennan, Sean

doi:10.1109/acc.2016.7525230

Cited by 17 publications

(10 citation statements)

References 10 publications

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“…Chuy et al applied the energy model of the vehicle to a single surface that was dependent on the linear velocity and turning radius terms [40]. Pentzer et al [41] developed the most recent method for addressing multiple surface types by using the kinematic model of a SAGV to estimate energy usage.…”

Section: Global Path Planningmentioning

confidence: 99%

An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

et al. 2021

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In recent years, the use of electric Autonomous Wheeled Mobile Robots (AWMRs) has dramatically increased in transport of the production chain. Generally, AWMRs must operate for several hours on a single battery charge. Since the energy density of the battery is limited, energy efficiency becomes a key element in improving material transportation performance during the manufacturing process. However, energy consumption is influenced by the navigation stages, because the type of motion necessary for the AWMR to perform during a mission is totally defined by these stages. Therefore, this paper analyzes methods of energy efficiency that have been studied recently for AWMR navigation stages. The selected publications are classified into planning and motion control categories in order to identify research gaps. Unlike other similar studies, this work focuses on these methods with respect to their implications for the energy consumption of AWMRs. In addition, by using an industrial Self-Guided Vehicle (SGV), we illustrate the direct influence of the motion planning stage on global energy consumption by means of several simulations and experiments. The results indicate that the reaction of the SGV in response to unforeseen obstacles can affect the amount of energy consumed. Hence, energy constraints must be considered when developing the motion planning of AWMRs.

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Section: Global Path Planningmentioning

confidence: 99%

An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

et al. 2021

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“…There have been several studies on trajectory generation of skid-steer mobile robots (Gupta et al , 2017; Hansen et al , 2012; Dogru and Marques, 2019; Wang and Qi, 2001; Pentzer et al , 2016). Distance optimal and energy optimal planning is experimentally tested on different fields and efficacy of energy optimal planning is presented (Pace et al , 2017).…”

Section: Guidance Techniques For Skid-steer Wheeled Mobile Robotsmentioning

confidence: 99%

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Khan

Malik

Raza

et al. 2020

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Purpose The purpose of this paper is to provide a comprehensive and unified presentation of recent developments in skid-steer wheeled mobile robots (SSWMR) with regard to its control, guidance and navigation for the researchers who wish to study in this field. Design/methodology/approach Most of the contemporary unmanned ground robot’s locomotion is based upon the wheels. For wheeled mobile robots (WMRs), one of the prominent and widely used driving schemes is skid steering. Because of mechanical simplicity and high maneuverability particularly in outdoor applications, SSWMR has an advantage over its counterparts. Different prospects of SSWMR have been discussed including its design, application, locomotion, control, navigation and guidance. The challenges pertaining to SSWMR have been pointed out in detail, which will seek the attention of the readers, who are interested to explore this area. Findings Relying on the recent literature on SSWMR, research gaps are identified that should be analyzed for the development of autonomous skid-steer wheeled robots. Originality/value An attempt to present a comprehensive review of recent advancements in the field of WMRs and providing references to the most intriguing studies.

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“…For another example, the robotic pose estimation, calculated by the kinematics model, which includes the slip parameters decided by the traversing terrains, usually benefits a lot from robotic terrain classification, especially in the situation without reliable global positioning systems [ 5 , 6 , 7 , 8 ]. Apart from hazards avoidance and pose estimation, many existing works have demonstrated that the performances of many other robotic fundamental functions, such as energy savings, route planning, gait control, etc., can be improved significantly from an accurate terrain classification method [ 9 , 10 , 11 , 12 , 13 ]. Therefore, terrain classification and its relevant research have received great attention from the DARPA Grand Challenge and Mars Exploration Plan [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Frequency-Temporal Disagreement Adaptation for Robotic Terrain Classification via Vibration in a Dynamic Environment

Chen

Jin-yi

et al. 2020

Sensors

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The accurate terrain classification in real time is of great importance to an autonomous robot working in field, because the robot could avoid non-geometric hazards, adjust control scheme, or improve localization accuracy, with the aid of terrain classification. In this paper, we investigate the vibration-based terrain classification (VTC) in a dynamic environment, and propose a novel learning framework, named DyVTC, which tackles online-collected unlabeled data with concept drift. In the DyVTC framework, the exterior disagreement (ex-disagreement) and interior disagreement (in-disagreement) are proposed novely based on the feature diversity and intrinsic temporal correlation, respectively. Such a disagreement mechanism is utilized to design a pseudo-labeling algorithm, which shows its compelling advantages in extracting key samples and labeling; and consequently, the classification accuracy could be retrieved by incremental learning in a changing environment. Since two sets of features are extracted from frequency and time domain to generate disagreements, we also name the proposed method feature-temporal disagreement adaptation (FTDA). The real-world experiment shows that the proposed DyVTC could reach an accuracy of 89.5%, but the traditional time- and frequency-domain terrain classification methods could only reach 48.8% and 71.5%, respectively, in a dynamic environment.

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Energy-based path planning for skid-steer vehicles operating in areas with mixed surface types

Cited by 17 publications

References 10 publications

An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

An Investigation into the Energy-Efficient Motion of Autonomous Wheeled Mobile Robots

Comprehensive study of skid-steer wheeled mobile robots: development and challenges

Frequency-Temporal Disagreement Adaptation for Robotic Terrain Classification via Vibration in a Dynamic Environment

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