A unified framework for operational range estimation of mobile robots operating on a single discharge to avoid complete immobilization

Tiwari, Kshitij; Xiao, Xuesu; Malik, Ashish; Chong, Nak Young

doi:10.1016/j.mechatronics.2018.12.006

Cited by 19 publications

(8 citation statements)

References 28 publications

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“…Empirical results are also presented in support of our model to validate the model fidelity. This work is a brief overview of our findings that were recently published in [11] and [12].…”

Section: Introductionmentioning

confidence: 87%

“…( 5), the generalized ancillary power model of Eq. ( 10) additionally considers the on-board computation cost and the communication overhead incurred due to data transmission as explained in [12].…”

Section: ) Energy Dissipation Modelmentioning

confidence: 99%

“…and the operational range estimate would be as good as the approximation. Depending on whether this integral is approximated with real-time mission data or approximated in one-shot by the human supervisor a priori, we get online or offline estimators, respectively, the details of which can be found in [12].…”

Section: ) Range Estimation Modelmentioning

confidence: 99%

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ORangE: Operational Range Estimation for Mobile Robot Exploration on a Single Discharge Cycle

Tiwari¹,

Xiao²,

Kyrki³

et al. 2019

Preprint

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This paper presents an approach for estimating the operational range for mobile robot exploration on a single battery discharge. Deploying robots in the wild usually requires uninterrupted energy sources to maintain the robot's mobility throughout the entire mission. However, due to unknown nature of the environments, recharging is usually not an option, due to the lack of pre-installed recharging stations or other mission constraints. In these cases, the ability to model the on-board energy consumption and estimate the operational range is crucial to prevent running out of battery in the wild. To this end, this work describes our recent findings that quantitatively break down the robot's on-board energy consumption and predict the operational range to guarantee safe mission completion on a single battery discharge cycle. Two range estimators with different levels of generality and model fidelity are presented, whose performances were validated on physical robot platforms in both indoor and outdoor environments. Model performance metrics are also presented as benchmarks.

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“…Empirical results are also presented in support of our model to validate the model fidelity. This work is a brief overview of our findings that were recently published in [11] and [12].…”

Section: Introductionmentioning

confidence: 87%

Section: ) Energy Dissipation Modelmentioning

confidence: 99%

See 1 more Smart Citation

ORangE: Operational Range Estimation for Mobile Robot Exploration on a Single Discharge Cycle

Tiwari¹,

Xiao²,

Kyrki³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Input Keyboard: This is the main driver circuit of the vehicle, by applying logic 1 to the microcontroller, dc power supply (Vcc) initiate the system. Global Positioning System (GPS) [21]: The GPS receiver calculates its position by precisely timing the signals sent by GPS satellites. The receiver utilizes the texts it gets to determine the travel time of each message and to calculate the receiver distance from each satellite.…”

Section: A System Descriptionmentioning

confidence: 99%

Development of a Prototype Autonomous Electric Vehicle

Mohammed

Abdullahi

Ibrahim

2021

jrc

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The paper presents an Autonomous Electric Vehicle with obstacle avoidance system. This research work made use of ultrasonic sensors, the principle of distance measurements and calculations as well as detecting obstacle on its path. The device consists of three ultrasonic sensors that detect object for each left, right and front of the vehicle, based on developed and installed codes in the Arduino microcontroller and displays the range using ISIS Proteus 8 electronic modelling software. The minimum and maximum range of object detections is 2cm to 400cm respectively. However, the measured distance was from 25cm to 150cm and the corresponding calculated distances using oscilloscope waveforms are 28.10cm and 148.3cm. The difference between the measured and calculated distance was 5.4% on average. GPS navigates the vehicle autonomously to its destination using an algorithm for navigation based on reactive behavior. The vehicle is powered by rechargeable batteries (4 lithium ion batteries) which are charged using external power source by connecting into electricity grid. Furthermore, a solar panel has been utilized as a secondary source of power to charge the batteries. This reduces the dependency of the vehicle on external power sources. The vehicle is capable of moving for about 20m to and fro and avoiding obstacle on its path.

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“…Safety, security, and rescue applications are example domains where robots are used to substitute human agents to undertake risk in dangerous, dirty, and dull (DDD) environments [1]. While guaranteeing safety by projecting human presence, the robots must also ensure their own safety at all times, in lieu of mission-critical or economic considerations.…”

Section: Introductionmentioning

confidence: 99%

Explicit Motion Risk Representation

Xiao

Dufek

Murphy

2019

2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR)

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This paper presents a formal definition and explicit representation of robot motion risk. Currently, robot motion risk has not been formally defined, but has already been used in motion and path planning. Risk is either implicitly represented as model uncertainty using probabilistic approaches, where the definition of risk is somewhat avoided, or explicitly modeled as a simple function of states, without a formal definition. In this work, we provide formal reasoning behind what risk is for robot motion and propose a formal definition of risk in terms of a sequence of motion, namely path. Mathematical approaches to represent motion risk are also presented, which is in accordance with our risk definition and properties. The definition and representation of risk provide a meaningful way to evaluate or construct robot motion or path plans. The understanding of risk is even of greater interest for the search and rescue community: the deconstructed environments cast extra risk onto the robot, since they are working under extreme conditions. A proper risk representation has the potential to reduce robot failure in the field.

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A unified framework for operational range estimation of mobile robots operating on a single discharge to avoid complete immobilization

Cited by 19 publications

References 28 publications

ORangE: Operational Range Estimation for Mobile Robot Exploration on a Single Discharge Cycle

ORangE: Operational Range Estimation for Mobile Robot Exploration on a Single Discharge Cycle

Development of a Prototype Autonomous Electric Vehicle

Explicit Motion Risk Representation

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