SlideShare a Scribd company logo
1 of 2
Download to read offline
23september 2016 • IEEE ROBOTICS & AUTOMATION MAGAZINE •
accurate traversal of all the trajecto-
ries was the winner.
2)	The Microassembly Challenge, in
which the microrobots assembled a
planar shape out of multiple
microscale components. This task
simulated anticipated applications
of microassembly for medical or
micromanufacturing applications.
3)	The MMC Showcase and Poster Ses-
sion, in which each team had an
opportunity to showcase and demon-
strate any advanced capabilities and
functionality of its microrobot sys-
tem. Each participating team and the
MMC organizers received one vote to
determine the Best in Show winner.
This year, three teams qualified for the
event: the University of Waterloo
Nanorobotic Group from Canada, the
Exemplary Indians from the Indian
Institute of Technology in Patna, and
Team UTV Romania from Valahia
University of Targoviste. To qualify, the
teams had to submit a qualification
video to the MMC organizers, demon-
strating the ability of their robots to
traverse the required sized trajectories,
and they had to be able to attend
MMC 2016. Out of the three qualify-
ing teams, Team UTV Romania won
both the Autonomous Mobility and
Accuracy Challenge and the Best in
Show, and the University of Waterloo
Nanorobotic Group won the Microas-
sembly Challenge.
MMC 2016, as well as previous
MMC events, helped to introduce
the general audience of the ICRA to
microrobotics and to disseminate
the excitement of this new and rap-
idly emerging field to the robotics
community. The MMC 2016 orga-
nizers, Prof. Igor Paprotny (Univer-
sity of Illinois at Chicago), Prof. Dave
Cappelleri (Purdue University, Indi-
ana), and Prof. Aaron Ohta (Univer-
sity of Hawaii), wish to congratulate
the winning teams and invite you all
to attend MMC 2017 at ICRA 2017
in Singapore!
The 2016 Humanitarian Robotics and
Automation Technology Challenge
By Edson Prestes, Lino Marques, Renata Neuland, Mathias Mantelli, Renan Maffei, Sedat Dogru,
José Prado, João Macedo, and Raj Madhavan
ccording to the United Na­­tions
Mine Action Service, land
mines kill 15,000–20,000
people every year and maim
countless more across 78 countries.
The cost involved in the demining pro-
cess is extremely high: in addition to
US$300–1,000 per mine, one person is
killed and two are injured for every
5,000 mines cleared. Therefore, clearing
postcombat regions of land mines has
proven to be a difficult, dangerous, and
expensive task with enormous social
implications for civilians. This scenario
motivated the RAS Special Interest
Group on Humanitarian Technology
(SIGHT) to organize the HRATC. The
third HRATC took place at ICRA 2016
in Stockholm, Sweden, on 17–18 May
2016, and it was preceded by almost
five months of preliminary practice and
test runs for the participating teams.
The previous two HRATCs took place
at the ICRA conferences held in Hong
Kong, China, and Seattle, Washington,
respectively [1], [2].
Our main goal is to promote global
awareness about the land-mine problem
and incentivize the robotics and auto-
mation community to join our initiative
in the development of robotic solutions
that can alleviate the consequences
caused by buried land mines. To make
this challenge viable and more afford-
able, a robust platform instrumented
with several sensors was made available
via simulation and (physical) testing
phases for anyone interested in joining
our effort, i.e., participants around the
globe could compete remotely in each
phase of the challenge. All teams had
access to the codes generated by the pre-
vious participants of the HRATC. This
enabled the development of algorithmic
solutions without reinventing the wheel,
and it resulted in more sophisticated
methodologies in a shorter duration.
The HRATC 2016 organizers coordi-
nated the simulation phase of the chal-
lenge from Brazil while the testing phase
was coordinated from Portugal on an
outdoor setup complete with mock land
mines that the robots were to identify via
metal detectors. During the final chal-
lenge phase, both teams of organizers in
their respective countries worked togeth-
er to run the challenge held in ICRA
2016 in Stockholm. The HRATC partici-
pants had the opportunity to see their
code run on the robot located in Portu-
gal in real time. All trials were beamed
via a YouTube channel to the conference
room through live streaming. After fin-
ishing each trial, team scores were deter-
mined according to the criteria, which
included exploration time, environmen-
tal coverage, detection and classification
quality, and land-mine avoidance.
At each of the HRATC events, the
difficulty level increased compared to
the previous one. For the 2016 chal-
lenge, the teams needed to sweep an
Digital Object Identifier 10.1109/MRA.2016.2587921
Date of publication: 13 September 2016
A
24 • IEEE ROBOTICS  AUTOMATION MAGAZINE • september 2016
arbitrary area defined by a list of posi-
tions provided by the global position-
ing system in search of land mines
placed in a nonuniform distribution.
The HRACT 2016 received nine entries
from five countries: Bangladesh,
France, India, Italy, and the United
States. After the simulation and testing
phases, four teams qualified for the
finals: DISHARI (Bangladesh), Tushar
(India), Autobots (India), and MavDe-
tectors (United States) (Figure 1). After
two intense days, Team Autobots was
declared the grand winner.
We believe that our challenge is a
good first step toward a better world
without land mines. We are hopeful
that, with continuous improvement in
each edition, we are on the right path
toward a version that could be deployed
in real scenarios with real land mines!
References
[1] R. Madhavan, L. Marques, E. Prestes, P.
Dasgupta, G. Cabrita, D. Portugal, B. Gouveia,
V. Jorge, R. Maffei, G. Franco, and J. Garcia,
“2014 Humanitarian Robotics and Automa-
tion Technology Challenge,” IEEE Robot.
Autom. Mag., vol. 21, no. 3, pp. 10–16, 2014.
[2] R. Madhavan, L. Marques, E. Prestes, R.
Maffei, V. Jorge, B. Gil, S. Dogru, G. Cabrita,
R. Neuland, and P. Dasgupta, “2015 Humani-
tarian Robotics and Automation Technology
Challenge,” IEEE Robot. Autom. Mag., vol. 22,
no. 3, pp. 182–184, 2015.
Figure 1. The HRATC finalists together with Edson Prestes (HRATC co-organizer, fourth
from the right) and Raj Madhavan (RAS-SIGHT chair, fifth from the left).
The 2016 Formal Methods for
Robotics Challenge
By Vasumathi Raman
R
obotic systems demand a high
standard of safety and correc­
tness of behavior. There is a
large body of algorithmic work
addressing the principled design of
correct-by-construction controllers for
robots, drawing on formal methods for
verification and automatic synthesis of
transition systems satisfying desired
properties. The first of its kind, the
FMRC was developed to address the
lack of large-scale demonstrations of
current capabilities in this domain and
of benchmarks and metrics for
evaluating novel algorithms.
At ICRA 2016, teams from four
universities—California Institute of
Technology (Caltech), Carnegie Mel-
lon University (CMU), Cornell Uni-
versity, and Worcester Polytechnic
Institute (WPI)—competed across two
problem domains designed to test vari-
ous challenges faced during the practi-
cal deployment of controller synthesis
approaches. The first domain involved
controlling a dynamical system mod-
eled as a chain of integrators to satisfy
a reach-avoid temporal logic specifi­
cation. This domain was designed to
test scalability of the submitted con­­
trol­ler synthesis methods on problem
instances of increasing dimension
and order of highest derivative. The
second domain was a road network
containing vehicles modeled as
Dubins cars. The objective was to con-
trol a single “ego” vehicle to achieve
safety (i.e., to not collide and to always
stay in its lane) and liveness (i.e., to
always eventually visit the goal
region) specifications while interact-
ing with the remaining vehicles,
whose behavior was uncontrolled but
simulated subject to certain assump-
tions (e.g., to always eventually vacate
the goal region).
To allow maximum flexibility of
solution format, the solutions were
evaluated by running them in a
black-box fashion rather than requir-
ing, e.g., solutions compatible with
Digital Object Identifier 10.1109/MRA.2016.2587958
Date of publication: 13 September 2016

More Related Content

Similar to 07565695

MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERING
MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERINGMODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERING
MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERINGIRJET Journal
 
20231019to20_OIP-2023_SFriedrichs.pdf
20231019to20_OIP-2023_SFriedrichs.pdf20231019to20_OIP-2023_SFriedrichs.pdf
20231019to20_OIP-2023_SFriedrichs.pdfSteffi Friedrichs
 
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...Ilona Anna Cieslik
 
Endangered Species Conservation
Endangered Species ConservationEndangered Species Conservation
Endangered Species ConservationIRJET Journal
 
IRJET - Swarm Robotic System for Mapping and Exploration of Extreme Envir...
IRJET -  	  Swarm Robotic System for Mapping and Exploration of Extreme Envir...IRJET -  	  Swarm Robotic System for Mapping and Exploration of Extreme Envir...
IRJET - Swarm Robotic System for Mapping and Exploration of Extreme Envir...IRJET Journal
 
Preprint-IC3I2022 - 14-16 Dec 2022.pdf
Preprint-IC3I2022 - 14-16 Dec 2022.pdfPreprint-IC3I2022 - 14-16 Dec 2022.pdf
Preprint-IC3I2022 - 14-16 Dec 2022.pdfChristo Ananth
 
Preprint-CSAE,China,21-23 October 2022.pdf
Preprint-CSAE,China,21-23 October 2022.pdfPreprint-CSAE,China,21-23 October 2022.pdf
Preprint-CSAE,China,21-23 October 2022.pdfChristo Ananth
 
Survey of accident detection systems
Survey of accident detection systemsSurvey of accident detection systems
Survey of accident detection systemsvivatechijri
 
Tsc cav@digital catapult_march2019
Tsc cav@digital catapult_march2019Tsc cav@digital catapult_march2019
Tsc cav@digital catapult_march2019Peter Bloomfield
 
Multi-function intelligent robotic in metals detection applications
Multi-function intelligent robotic in metals detection applicationsMulti-function intelligent robotic in metals detection applications
Multi-function intelligent robotic in metals detection applicationsTELKOMNIKA JOURNAL
 
A multi-objective evolutionary scheme for control points deployment in intell...
A multi-objective evolutionary scheme for control points deployment in intell...A multi-objective evolutionary scheme for control points deployment in intell...
A multi-objective evolutionary scheme for control points deployment in intell...IJECEIAES
 
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...Towards a Smart (City) Data Science. A case-based retrospective on policies, ...
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...Enrico Daga
 
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...University of Piraeus
 
Autonomous vehicle implementation
Autonomous vehicle implementationAutonomous vehicle implementation
Autonomous vehicle implementationEnsaf Atef
 
The 2009 Simulated Car Racing Championship
The 2009 Simulated Car Racing ChampionshipThe 2009 Simulated Car Racing Championship
The 2009 Simulated Car Racing ChampionshipDavide Ciambelli
 
IRJET- Path Finder with Obstacle Avoidance Robot
IRJET-  	  Path Finder with Obstacle Avoidance RobotIRJET-  	  Path Finder with Obstacle Avoidance Robot
IRJET- Path Finder with Obstacle Avoidance RobotIRJET Journal
 
Problems in Autonomous Driving System of Smart Cities in IoT
Problems in Autonomous Driving System of Smart Cities in IoTProblems in Autonomous Driving System of Smart Cities in IoT
Problems in Autonomous Driving System of Smart Cities in IoTijtsrd
 
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1NanubalaDhruvan
 

Similar to 07565695 (20)

MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERING
MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERINGMODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERING
MODERN TECHNOLOGIES USE IN TRANSPORTATION ENGINEERING
 
20231019to20_OIP-2023_SFriedrichs.pdf
20231019to20_OIP-2023_SFriedrichs.pdf20231019to20_OIP-2023_SFriedrichs.pdf
20231019to20_OIP-2023_SFriedrichs.pdf
 
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...
ITS 2018 Denmark Publication: Advancing active safety and testing methodologi...
 
Endangered Species Conservation
Endangered Species ConservationEndangered Species Conservation
Endangered Species Conservation
 
IRJET - Swarm Robotic System for Mapping and Exploration of Extreme Envir...
IRJET -  	  Swarm Robotic System for Mapping and Exploration of Extreme Envir...IRJET -  	  Swarm Robotic System for Mapping and Exploration of Extreme Envir...
IRJET - Swarm Robotic System for Mapping and Exploration of Extreme Envir...
 
Preprint-IC3I2022 - 14-16 Dec 2022.pdf
Preprint-IC3I2022 - 14-16 Dec 2022.pdfPreprint-IC3I2022 - 14-16 Dec 2022.pdf
Preprint-IC3I2022 - 14-16 Dec 2022.pdf
 
Preprint-CSAE,China,21-23 October 2022.pdf
Preprint-CSAE,China,21-23 October 2022.pdfPreprint-CSAE,China,21-23 October 2022.pdf
Preprint-CSAE,China,21-23 October 2022.pdf
 
Survey of accident detection systems
Survey of accident detection systemsSurvey of accident detection systems
Survey of accident detection systems
 
Tsc cav@digital catapult_march2019
Tsc cav@digital catapult_march2019Tsc cav@digital catapult_march2019
Tsc cav@digital catapult_march2019
 
Multi-function intelligent robotic in metals detection applications
Multi-function intelligent robotic in metals detection applicationsMulti-function intelligent robotic in metals detection applications
Multi-function intelligent robotic in metals detection applications
 
SMARTI
SMARTISMARTI
SMARTI
 
A multi-objective evolutionary scheme for control points deployment in intell...
A multi-objective evolutionary scheme for control points deployment in intell...A multi-objective evolutionary scheme for control points deployment in intell...
A multi-objective evolutionary scheme for control points deployment in intell...
 
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...Towards a Smart (City) Data Science. A case-based retrospective on policies, ...
Towards a Smart (City) Data Science. A case-based retrospective on policies, ...
 
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
A Route Selection Scheme for supporting Virtual Tours in Sites with Cultural ...
 
PROSPECT - PROactive Safety for PEdestrians and CyclisTs
PROSPECT - PROactive Safety for PEdestrians and CyclisTsPROSPECT - PROactive Safety for PEdestrians and CyclisTs
PROSPECT - PROactive Safety for PEdestrians and CyclisTs
 
Autonomous vehicle implementation
Autonomous vehicle implementationAutonomous vehicle implementation
Autonomous vehicle implementation
 
The 2009 Simulated Car Racing Championship
The 2009 Simulated Car Racing ChampionshipThe 2009 Simulated Car Racing Championship
The 2009 Simulated Car Racing Championship
 
IRJET- Path Finder with Obstacle Avoidance Robot
IRJET-  	  Path Finder with Obstacle Avoidance RobotIRJET-  	  Path Finder with Obstacle Avoidance Robot
IRJET- Path Finder with Obstacle Avoidance Robot
 
Problems in Autonomous Driving System of Smart Cities in IoT
Problems in Autonomous Driving System of Smart Cities in IoTProblems in Autonomous Driving System of Smart Cities in IoT
Problems in Autonomous Driving System of Smart Cities in IoT
 
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1
TRAFFIC MANAGEMENT THROUGH SATELLITE IMAGING -- Part 1
 

07565695

  • 1. 23september 2016 • IEEE ROBOTICS & AUTOMATION MAGAZINE • accurate traversal of all the trajecto- ries was the winner. 2) The Microassembly Challenge, in which the microrobots assembled a planar shape out of multiple microscale components. This task simulated anticipated applications of microassembly for medical or micromanufacturing applications. 3) The MMC Showcase and Poster Ses- sion, in which each team had an opportunity to showcase and demon- strate any advanced capabilities and functionality of its microrobot sys- tem. Each participating team and the MMC organizers received one vote to determine the Best in Show winner. This year, three teams qualified for the event: the University of Waterloo Nanorobotic Group from Canada, the Exemplary Indians from the Indian Institute of Technology in Patna, and Team UTV Romania from Valahia University of Targoviste. To qualify, the teams had to submit a qualification video to the MMC organizers, demon- strating the ability of their robots to traverse the required sized trajectories, and they had to be able to attend MMC 2016. Out of the three qualify- ing teams, Team UTV Romania won both the Autonomous Mobility and Accuracy Challenge and the Best in Show, and the University of Waterloo Nanorobotic Group won the Microas- sembly Challenge. MMC 2016, as well as previous MMC events, helped to introduce the general audience of the ICRA to microrobotics and to disseminate the excitement of this new and rap- idly emerging field to the robotics community. The MMC 2016 orga- nizers, Prof. Igor Paprotny (Univer- sity of Illinois at Chicago), Prof. Dave Cappelleri (Purdue University, Indi- ana), and Prof. Aaron Ohta (Univer- sity of Hawaii), wish to congratulate the winning teams and invite you all to attend MMC 2017 at ICRA 2017 in Singapore! The 2016 Humanitarian Robotics and Automation Technology Challenge By Edson Prestes, Lino Marques, Renata Neuland, Mathias Mantelli, Renan Maffei, Sedat Dogru, José Prado, João Macedo, and Raj Madhavan ccording to the United Na­­tions Mine Action Service, land mines kill 15,000–20,000 people every year and maim countless more across 78 countries. The cost involved in the demining pro- cess is extremely high: in addition to US$300–1,000 per mine, one person is killed and two are injured for every 5,000 mines cleared. Therefore, clearing postcombat regions of land mines has proven to be a difficult, dangerous, and expensive task with enormous social implications for civilians. This scenario motivated the RAS Special Interest Group on Humanitarian Technology (SIGHT) to organize the HRATC. The third HRATC took place at ICRA 2016 in Stockholm, Sweden, on 17–18 May 2016, and it was preceded by almost five months of preliminary practice and test runs for the participating teams. The previous two HRATCs took place at the ICRA conferences held in Hong Kong, China, and Seattle, Washington, respectively [1], [2]. Our main goal is to promote global awareness about the land-mine problem and incentivize the robotics and auto- mation community to join our initiative in the development of robotic solutions that can alleviate the consequences caused by buried land mines. To make this challenge viable and more afford- able, a robust platform instrumented with several sensors was made available via simulation and (physical) testing phases for anyone interested in joining our effort, i.e., participants around the globe could compete remotely in each phase of the challenge. All teams had access to the codes generated by the pre- vious participants of the HRATC. This enabled the development of algorithmic solutions without reinventing the wheel, and it resulted in more sophisticated methodologies in a shorter duration. The HRATC 2016 organizers coordi- nated the simulation phase of the chal- lenge from Brazil while the testing phase was coordinated from Portugal on an outdoor setup complete with mock land mines that the robots were to identify via metal detectors. During the final chal- lenge phase, both teams of organizers in their respective countries worked togeth- er to run the challenge held in ICRA 2016 in Stockholm. The HRATC partici- pants had the opportunity to see their code run on the robot located in Portu- gal in real time. All trials were beamed via a YouTube channel to the conference room through live streaming. After fin- ishing each trial, team scores were deter- mined according to the criteria, which included exploration time, environmen- tal coverage, detection and classification quality, and land-mine avoidance. At each of the HRATC events, the difficulty level increased compared to the previous one. For the 2016 chal- lenge, the teams needed to sweep an Digital Object Identifier 10.1109/MRA.2016.2587921 Date of publication: 13 September 2016 A
  • 2. 24 • IEEE ROBOTICS AUTOMATION MAGAZINE • september 2016 arbitrary area defined by a list of posi- tions provided by the global position- ing system in search of land mines placed in a nonuniform distribution. The HRACT 2016 received nine entries from five countries: Bangladesh, France, India, Italy, and the United States. After the simulation and testing phases, four teams qualified for the finals: DISHARI (Bangladesh), Tushar (India), Autobots (India), and MavDe- tectors (United States) (Figure 1). After two intense days, Team Autobots was declared the grand winner. We believe that our challenge is a good first step toward a better world without land mines. We are hopeful that, with continuous improvement in each edition, we are on the right path toward a version that could be deployed in real scenarios with real land mines! References [1] R. Madhavan, L. Marques, E. Prestes, P. Dasgupta, G. Cabrita, D. Portugal, B. Gouveia, V. Jorge, R. Maffei, G. Franco, and J. Garcia, “2014 Humanitarian Robotics and Automa- tion Technology Challenge,” IEEE Robot. Autom. Mag., vol. 21, no. 3, pp. 10–16, 2014. [2] R. Madhavan, L. Marques, E. Prestes, R. Maffei, V. Jorge, B. Gil, S. Dogru, G. Cabrita, R. Neuland, and P. Dasgupta, “2015 Humani- tarian Robotics and Automation Technology Challenge,” IEEE Robot. Autom. Mag., vol. 22, no. 3, pp. 182–184, 2015. Figure 1. The HRATC finalists together with Edson Prestes (HRATC co-organizer, fourth from the right) and Raj Madhavan (RAS-SIGHT chair, fifth from the left). The 2016 Formal Methods for Robotics Challenge By Vasumathi Raman R obotic systems demand a high standard of safety and correc­ tness of behavior. There is a large body of algorithmic work addressing the principled design of correct-by-construction controllers for robots, drawing on formal methods for verification and automatic synthesis of transition systems satisfying desired properties. The first of its kind, the FMRC was developed to address the lack of large-scale demonstrations of current capabilities in this domain and of benchmarks and metrics for evaluating novel algorithms. At ICRA 2016, teams from four universities—California Institute of Technology (Caltech), Carnegie Mel- lon University (CMU), Cornell Uni- versity, and Worcester Polytechnic Institute (WPI)—competed across two problem domains designed to test vari- ous challenges faced during the practi- cal deployment of controller synthesis approaches. The first domain involved controlling a dynamical system mod- eled as a chain of integrators to satisfy a reach-avoid temporal logic specifi­ cation. This domain was designed to test scalability of the submitted con­­ trol­ler synthesis methods on problem instances of increasing dimension and order of highest derivative. The second domain was a road network containing vehicles modeled as Dubins cars. The objective was to con- trol a single “ego” vehicle to achieve safety (i.e., to not collide and to always stay in its lane) and liveness (i.e., to always eventually visit the goal region) specifications while interact- ing with the remaining vehicles, whose behavior was uncontrolled but simulated subject to certain assump- tions (e.g., to always eventually vacate the goal region). To allow maximum flexibility of solution format, the solutions were evaluated by running them in a black-box fashion rather than requir- ing, e.g., solutions compatible with Digital Object Identifier 10.1109/MRA.2016.2587958 Date of publication: 13 September 2016