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Table 2 Comparing some of the main related works based on their experimental characteristics

From: Multi-Agent Foraging: state-of-the-art and research challenges

  

Platform

Size and limits of the world

Number and nature of food

Max number of robots

Robot characteristics

Energy of the robot

Scalability

Performance metrics

Computer simulation

         
 

Hoff et al. (2013)

Own developed multi-agent simulator

10 m \(\times \) 10 m continuous

One unlimited

20

E-Puck, sensors for nest, food, and obstacles in direct proximity, communicate with nearby robots, measure the range and bearing from which each transmission came. Robots do not have global position measurement or global communication

Unlimited

N/A

Food found or not, How quickly food is found, the rate at which it returned the food to the nest

 

Lee et al. (2013)

Stage/Player

Circle of radius = 80 continuous

One food is generated at a random position per ten seconds

40

Agents can store information, sense locally their world and communicate with each other in unlimited range

Limited

Consider 25, 30, 35 and 40 agents

Energy efficiency

 

Magdy et al. (2013)

Own developed multi-agent simulator

N/A

One limited at fixed position

50

Agents are Turing machine equivalent which can communicate with nearby robots

Unlimited

Consider 10, 20, 25, 30, 40 and 50 agents

Food found or not at limited time, speed to find food

 

Pitonakova et al. (2014)

Own developed multi-agent simulator

4000 \(\times \) 4000 continuous-space with periodic boundaries

Between 10 and 100 deposits with varied quality

100

Size 10 \(\times \) 10 units, subsumption architecture, initially randomly oriented, carry one unit, odometry, memory to store energy efficiency of a deposits

Limited

Consider 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 agents

Proportion of collected food

 

Simonin et al. (2014)

TurtleKit simulation platform

2D bounded grid of varied size 25 \(\times \) 25 cells to 800 \(\times \) 800 cells

20 with 10 units and 20 units each randomly distributed

160

Subsumption architecture, size of one cell, memory less, perceive the four neighboring cells, write on current cell integer value (APF value), read from cell, color trails with specific color, detect and follow trails, one cell can contain multiple agents

Unlimited

Consider 5, 10, 20, 40, 80 and 160 agents

Average foraging time

 

Zedadra et al. (2016)

Netlogo simulator

2D bounded grid of varied size 100 \(\times \) 100 cells to 1200 \(\times \) 1200 cells

1 to 10 sites with 500 to 1500 units

10,000

Subsumption architecture, size of one cell, memory less, perceive the four neighboring cells, deposit a pheromone on current cell, color trails with specific color, detect and follow trails, one cell can contain multiple agents

Unlimited

Consider 1 to 10000 agents

Average Foraging Time, Total Food Returned, Average Path Length

 

Zedadra et al. (2016)

Netlogo simulator

2D bounded grid of varied size 100 \(\times \) 100 cells to 1000 \(\times \) 1000 cells

1 to 10 locations, each with 500 units

1000

Subsumption architecture, size of one cell, memory less, perceive the four neighboring cells, deposit a pheromone on current cell, color trails with specific color, detect and follow trails, one cell can contain multiple agents

Limited

Consider 100 to 1000 agents

Total energy consumed, energy efficiency

 

Johnson and Brown (2016)

Enki 2.0 robot simulator

Circularly bounded 2D environment

Cylinders with a diameter of 10 cm

N/A

Enki’s e-puck model which have a diameter of 7.4 cm, inter-wheel distance of 5.1 cm, and weight of 152 g

Unlimited

N/A

Cluster targets to specific location

Real experiments

         
 

Alers et al. (2014)

Turtlebot platform

Bounded 2D environment

One limited food

4

Turtlebot equipped with a laptop with a core-i3 CPU for computation, Kinect sensor, RGBD information used to detect and locate AR markers, wheel odometry and gyro information, six unique markers, toolkit called ALVAR, wi- with a UDP connection

Unlimited

N/A

Did robots converge to foraging

 

Geuther et al. (2012)

Lego Mindstorms NXT kits

50x50 grid

Energy spots

Scouts: 25;Harvesters: 60

USB port and Bluetooth module to communicate with a central system, IR light sources, compass sensor

Unlimited

Varying scouts 5, 10, 15, 20 and 25; Varying harvesters 20, 30, 40, 50 and 60

Total energy harvested

 

Pitonakova et al. (2016)

ARGoS simulation environment

Continuous space and updates itself 10 times per second, 50 m 50 m

N deposit with volume v and quality Q varied at each simulation

25

MarXbot robots, differentially steered with a diameter of 0.17 m, four color sensors pointed to the g round, 2 4 infrared proximity sensors, light sensor used for navigation towards the base, a range and b earing module, wheel-mounted sensors utilized for odometry and a ring of eight color LEDs used for debugging

Unlimited

N/A

Resource collected

 

Russell et al. (2015)

N/A

Continuous real world with 28 pre-deployed beacons

One food

8

Differential drive robots of authors own design, capable of grasping a single beacon, moving it from place to place, Arduino Uno micro-controller coupled with a Raspberry Pi Linux computer, outfitted with a camera, 802.11 wireless communication, USB interfaces, five Sharp IR infrared distance sensors, two simple bump sensors, two encoded wheels, an embedded gripper capable of collecting small cans, a flat push surface, and an I2C-driven display, outfitted with a Tmote Sky wireless sensor mote attached to the Raspberry Pi, sensor motes communicated over 802.15.4, channel 26, via UDP multi-cast

Unlimited

Varying 1, 2, 4, and 8 robots

Total food pellets gathered so far

 

Heinerman et al. (2016)

N/A

1 \(\times \) 1 m arena

One target

6

Thymio II robot, seven Infra-Red (IR) proximity sensors for obstacle detection, differential drive with the maximum wheel actuators set between −500 and 500, a cam-era, wireless communication, and a high capacity battery, A WiFi dongle for communication, battery, allowing for a total experimental time of 10 hours, LEGO gripper

Limited

N/A

Number of pucks collected in ten-minute intervals