[robotics-worldwide] [jobs] PhD opening in Reactive Trajectory Planning Methods for Formation Control and Localization of Multi-Robot System

Paolo Robuffo Giordano paolo.robuffo_giordano at irisa.fr
Mon Mar 18 09:50:04 PDT 2019




The Rainbow team at Inria/IRISA Rennes, France


https://urldefense.proofpoint.com/v2/url?u=https-3A__team.inria.fr_rainbow_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=D4zXYPiDbKOtLDT93opFy5FHT97dehKfrD01FymOteE&e=


is looking for a PhD candidate in *Reactive Trajectory Planning Methods 
for Formation Control and Localization of Multi-Robot System*




*********** CONTEXT ***********


The main basic problems when addressing decentralized (and sensor-based) 
formation control for multiple robots are two: formation control and 
relative localization. Formation control is the problem of devising 
control strategies for attaining some desired geometric arrangement in 
space (e.g., a target shape). Relative localization is the problem of 
estimating/recovering the robot relative poses from the available 
onboard sensor measurements (typically, distances or bearing angles). 
Once one is able to solve these two problems, much more complex 
tasks/missions become possible (e.g., exploration, patrolling, coverage, 
but also cooperative manipulation).
The localization and formation control problems are intimately related: 
any formation controller needs availability of the robot relative poses 
which must be estimated/recovered from the sensor measurements. However, 
the localization itself is a nonlinear estimation problem and, 
therefore, the motion/trajectory followed by the robots (i.e., the 
action imposed by the formation controller) has a strong impact in the 
performance/accuracy/convergence rate of the relative pose estimation. 
This tight loop between formation control and estimation (which is the 
multi-robot version of the classical “action/perception loop” in 
robotics) is both scientifically very interesting and practically very 
relevant (one needs to properly solve it for having the hope of 
deploying multi-robot teams in real-world conditions).


The vast majority of formation control and localization algorithms are 
essentially local: they aim at obtaining the best control 
actions/estimations “right now” given the current state of the robot 
group, but they cannot reason about the future. However, since several 
years many modern control approaches for non-trivial robotics 
applications stress the importance of a proper trajectory planning for 
accomplishing a task in more robust and effective ways. Indeed, 
(reactive) trajectory planning allows to reason about the future 
consequences of local actions, to better take into account complex 
constraints (e.g., obstacle avoidance, limited actuation, sensing 
constraints), and, finally, to attain optimality w.r.t. criteria of 
interest (e.g., time, energy, control effort).


While reactive trajectory planning approaches (or Model Predictive 
Control – MPC) have gained a lot of ground in the robotics field (one 
example for all, humanoid robotics), their use in the context of 
multi-robot formation control and localization is still quite limited. 
On the other hand, the complexity of controlling a multi-robot group in 
harsh environments (sensing constraints, limited 
actuation/communication/processing power, obstacle and self-collision 
avoidance, need to estimate some group properties at runtime) would 
clearly call for the use of modern reactive trajectory planning 
approaches in order to better deal with the problems of formation 
control and localization in unstructured environments. This is not a 
trivial issue, since one has to address all the typical 
sensing/communication constraints of multi-robots, as well as comply 
with the requirements of decentralization and scalability (i.e., 
ideally, each robot should be able to plan its own future trajectory by 
only exploiting sensed/communicated information from the closest neighbors).




*********** PHD TOPIC ***********


In this context, the goal of this PhD thesis is to close this gap and 
develop novel reactive trajectory planning algorithms tailored to the 
multi-robot case. These algorithms should allow for an effective 
resolution of the “multi-robot perception/action loop”, i.e., formation 
control and localization, in realistic settings: limited sensing (e.g., 
fov, range), limited actuation, limited communication, presence of 
obstacles. Global objectives (e.g., exploration/patrolling) or 
optimality criteria (e.g., energy consumption, localization accuracy) 
should also be taken into account.

The PhD activities will naturally leverage the strong internal 
competences on multi-robot control/optimal estimation and on trajectory 
planning, and will be performed in cooperation with the Chorale team at 
Inria Sophia Antipolis (in particular P. Salaris as co-supervisor). The 
devised algorithms will be first tested in a simulation environment and 
then implemented and validated on the several quadrotor UAVs available 
in the team (in an indoor motion capture arena).




*********** CANDIDATE'S EXPECTED PROFILE ***********


The candidate must be a proficient user of C/C++ and ROS. Familiarity 
with matlab/simulink is a plus. Scientific curiosity, large autonomy and 
ability to work independently are also expected.

A M.Sc. degree in computer science, robotics, engineering, applied 
mathematics (or related fields) is required.

The PhD aims at advancing the state-of-the-art from both the 
*methodological/theoretical* and experimental points of view.
Therefore, a strong passion (and attitude) towards the *more theoretical 
and algorithmic side* of robotics (nonlinear control, estimation, 
planning) is expected.




*********** SALARY ***********

The position is full-time for 3 years and will be paid according to the 
French salary regulations for PhD students.




***********  ENVIRONMENT ***********


The Rainbow team

https://urldefense.proofpoint.com/v2/url?u=https-3A__team.inria.fr_rainbow_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=D4zXYPiDbKOtLDT93opFy5FHT97dehKfrD01FymOteE&e=

is internationally recognized for its scientific activity as well as for 
technology transfer experiences in the field of visual tracking, visual 
servoing, computer vision and sensor-based control for robotics 
applications. The facilities available in the group include three 6-dof 
industrial manipulator arms, a 6-dof torque-controlled backdrivable arm, 
two 7-dof torque-controlled robot arm (Franka), a pioneer indoor mobile 
robot, two humanoid robots (Romeo and Pepper), a fleet of quadrotor 
UAVs, and an indoor testing arena instrumented with Vicon.


The candidates will be under the supervision of


*Dr. Paolo Robuffo Giordano*

https://urldefense.proofpoint.com/v2/url?u=https-3A__team.inria.fr_rainbow_team_prg_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=m4F6hnjmoqk0xF4SVQe8sDSgpDH1NubvigKbxqViDRA&e=

and

*Dr. Paolo Salaris*

https://urldefense.proofpoint.com/v2/url?u=https-3A__project.inria.fr_chorale_members_paolo-2Dsalaris_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=xr4FFCfYAHZaIwySBkDoVD8YMlxIUuaH16xYosX2_TE&e=


and will work in close collaboration with other members of the Rainbow 
group involved in the project.


The Rainbow group is part of the Inria/Irisa lab that spreads its 
activities in 30 research teams working in computer science, signal 
processing, and control. It involves about 650 people, including 120 
professors and assistant professors, 100 full-time researchers, 80 
administrative staff, and 250 PhD students.




***********  HOW TO APPLY  ***********

Instructions on how to apply can be found at


https://urldefense.proofpoint.com/v2/url?u=https-3A__team.inria.fr_rainbow_phd-2Dmulti-2Drobot-2Dplanning_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=84DGaOke9rXVX4qZiLEjDwH6LlCa456Ez9p_zYylQDA&e=


The position will remain open until a satisfactory candidate is found





-- 
Dr. Paolo Robuffo Giordano

Centre National de la Recherche Scientifique (CNRS)
Rainbow Team, Irisa and Inria Bretagne Atlantique
Campus Universitaire de Beaulieu
35042 Rennes cedex, France
Tel: +33 (0)2 99842545
Fax: +33 (0)2 99847171
Email: prg at irisa.fr
Website: https://urldefense.proofpoint.com/v2/url?u=https-3A__team.inria.fr_rainbow_team_prg_&d=DwIDaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=5fbwhn1qad9S1uze2Q5zL1YTAD8TNL1Ekhiy6c-AtiA&s=m4F6hnjmoqk0xF4SVQe8sDSgpDH1NubvigKbxqViDRA&e=
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