Panthera: Design of a Reconfigurable Pavement Sweeping Robot

Hayat, Abdullah Aamir; Parween, Rizuwana; Elara, Mohan Rajesh; Parsuraman, K.; Kandasamy, Prathap

doi:10.1109/icra.2019.8794268

Cited by 28 publications

(22 citation statements)

References 9 publications

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“…whered i is the 3 × 3 skew-symmetric cross product matrix associated with the vector d i . Substituting Equations (10) and (11) into Equations (7) and (8) , the NE equations of motion for the ith link can be represented with respect to the origin O i as…”

Section: Newton-euler Equations Of Motionmentioning

confidence: 99%

“…The four omni-wheels in each module will provide mechanical stability to the base along with the higher acceleration over the three omni-wheels [10]. The pavement sweeping robot with reconfigurability and differential wheels were presented in [11]. The matrices for analyzing the performance are, measurement of the covered area using computer vision technique and the distance covered by the cleaning robot [12] which depends on the energy consumption.…”

Section: Introductionmentioning

confidence: 99%

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Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption

et al. 2019

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The autonomous floor-cleaning self-reconfigurable robots have entered into the practical stage by establishing enhanced area coverage over the fixed morphology counterparts. Energy consumption during the self-reconfiguration, i.e., changing the shape of the robot from one form to another, becomes a primary focus in these robots that carry finite energy sources. In this paper, hTetro platform with two hinge dissections namely, Left–Left–Left (LLL) and Left–Left–Right (LLR) are modeled and assessed for the energy consumption during the reconfiguration. The geometry of the two dissections, its workspaces, and the set of inverse kinematics solutions for the seven forms are presented. The inverse dynamics using the Newton–Euler approach was adopted to calculate the wrench, i.e., forces and moments at the hinge joints, and subsequently assess the power consumed during the reconfigurations of two hinge dissections in the simulation. Extensive experiments were performed across the two assembled platforms to estimate the power consumption by logging the current data. The comparison was made with the simulation results. The results are particularly useful in the selection of reconfiguration with minimal energy consumption during the floor cleaning.

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Section: Newton-euler Equations Of Motionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption

et al. 2019

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“…Due to long working hours, low wages, unwillingness to work as a cleaner, workforce shortage has been a constant problem for food court cleaning and maintenance tasks in recent times [1]. Recently, many robotic platforms are designed for different cleaning application which include floor cleaning [2,3], facade cleaning [4], staircase cleaning [5], pavement cleaning [6,7] and garden cleaning [8]. However, these robot architectures could not support table cleaning and maintenance tasks.…”

Section: Introductionmentioning

confidence: 99%

Table Cleaning Task by Human Support Robot Using Deep Learning Technique

Yin

Apuroop

Tamilselvam

et al. 2020

Sensors

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This work presents a table cleaning and inspection method using a Human Support Robot (HSR) which can operate in a typical food court setting. The HSR is able to perform a cleanliness inspection and also clean the food litter on the table by implementing a deep learning technique and planner framework. A lightweight Deep Convolutional Neural Network (DCNN) has been proposed to recognize the food litter on top of the table. In addition, the planner framework was proposed to HSR for accomplishing the table cleaning task which generates the cleaning path according to the detection of food litter and then the cleaning action is carried out. The effectiveness of the food litter detection module is verified with the cleanliness inspection task using Toyota HSR, and its detection results are verified with standard quality metrics. The experimental results show that the food litter detection module achieves an average of 96% detection accuracy, which is more suitable for deploying the HSR robots for performing the cleanliness inspection and also helps to select the different cleaning modes. Further, the planner part has been tested through the table cleaning tasks. The experimental results show that the planner generated the cleaning path in real time and its generated path is optimal which reduces the cleaning time by grouping based cleaning action for removing the food litters from the table.Sensors 2020, 20, 1698 2 of 20 vision-based techniques are widely used in cleaning robots for recognizing the litter and compute the cleaning action [14][15][16][17][18][19]. Andersen et al., built up a visual cleaning map for cleaning robots using a vision algorithm and a powerful light-transmitting diode. The sensor recognizes the grimy region and generates the dirt map by examining the surface pictures pixel-by-pixel utilizing the multi-variable statistical method [15]. David et al., proposed high-level manipulation actions for cleaning dirt from table surfaces using REEM a humanoid service robot. The author uses a background subtraction algorithm for recognizing the dirt from the table and Noisy Indeterministic Deictic (NID) rules-based learning algorithm to generate the sequence of cleaning action [16]. Ariyan et al., developed a planning algorithm for the removal of stains from non-planar surfaces where the author uses a depth-first branch-and-bound search to generate cleaning trajectories with the K-means clustering algorithm [17]. Hass et al., demonstrated the use of unsupervised clustering algorithm and Markov Decision Problem (MDP) for performing the cleaning task where unsupervised clustering algorithm is used to distinguish the dirt from surface and MDP algorithm is used to generate the maps, and transition model from clustered image is used to describe the robot cleaning action [18]. Nonetheless, these approaches have some practical issues and disadvantages for using in food court table cleaning; the detection ratio relies heavily on the textured surfaces, which makes it challenging to identify the litter type as solid...

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“…There are number reconfigurable robots such as CEBOT [6], Millibot [7], Crystalline [8], ATRON [9], hTetro [10]. The reconfigurable robot for the pavement sweeping task was first reported in [11] where only the mechanical layout and its features where discussed.…”

Section: Introductionmentioning

confidence: 99%

“…In this study, besides giving the description in detail the previous initial work of a pavement cleaning robot called Panthera [11] which can change the width of the robot's frame as in Fig. 2 to suit the environmental conditions, we have defined the operating primitives of the Panthera robot locomotion on the pavement.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Pavement Sweeping Robot and Pedestrian Cohabitant Framework by Vision Techniques

Hayat

Elara

et al. 2019

IEEE Access

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The periodic cleaning pavement is a requirement for a clean environment in urban areas. The robot named Panthera introduced in this paper has the ability to change the width of the frame to help the cleaning tasks become suitable for different pavement types and friendly with the activities of the pedestrian. The Panthera cleaning operations which allow pedestrian walks freely on the pavement is modeled as a pedestrian robot cohabitant framework. To this end, the mask based deep convolutional neural network (DCNN) is used to archive segmented label maps of pedestrians in color image, then the distance from detected objects to the robot is estimated and tracked by averaging filtered depth values in the corresponding region in the refined depth image. The width and the distance from the robot to the approaching pedestrians are used to adjust the robot width. The enlarging and squeezing operations of the Panthera width are conducted by rotating one motor to change the length of the lead screw rod and the angle linkage hinges from the information of encoders sensors. The experiments carried out on real environments demonstrated the autonomous avoiding pedestrians ability by the kinematic model of Panthera.

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Panthera: Design of a Reconfigurable Pavement Sweeping Robot

Cited by 28 publications

References 9 publications

Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption

Modeling and Assessing of Self-Reconfigurable Cleaning Robot hTetro Based on Energy Consumption

Table Cleaning Task by Human Support Robot Using Deep Learning Technique

Reconfigurable Pavement Sweeping Robot and Pedestrian Cohabitant Framework by Vision Techniques

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