01/16¶

Participants:

• From MAG: Vincent Bissonnette, Clément Bazerque, Raphaël (?)
• From LAAS: Andrea, Ellon, Quentin

Goal of the meeting: As we are going to test our algorithm chains in MORSE, we need to coordinate our effort on the simulator and collaborate where we can. As Clément already started working full-time on MORSE, we went there to see what was already available and how we can catch-up and improve.

MORSE at MAG¶

MAG's goal at the moment is to produce a full working chain integrated into MORSE (and if possible, with our help, directly on our rovers), by the end of February. The first version of the processing chains they want to integrate is the following:

Stereovision => Disparity computation => DEM building => Navigation Map => Path planning => Motion control

All the algorithms come from CNES and need integration inside MORSE. The following sensor/actuator flows are already implemented:

• Lidar
• Stereobench
• Pan-tilt unit
• Robot control (did not ask which one, but from Simon's report it is a RMP440)

At the moment, the interface between MORSE and the algorithms is made via YARP, but they are working on an interface with ROS. The orchestration of scenarios is made through a simple state-machine written in Python. The scenario implemented so far is "Acquire a scan and move forward for a given distance". No localization is performed in MORSE.The pose of the robot is directly given through MORSE and does not come from a MAG algorithm. The machine has then two states:

• Move pan-tilt
• Go to point

Concerning datatypes: Right now, they are not using ASN.1 compliant datatypes. Vincent told us that the ESROCOS ASN.1 compiler exists but the did not interface anything with the C struct produced. He proposes that we use ROS datatypes for now and see for interfacing properly afterwards. We agreed on this.

How LAAS can contribute¶

*First thing is to provide MAG with accurate simulations of our rovers, in order to test their algorithms and ease integration directly on the rover. They require:

• Sensor streams:
  • Velodyne
  • Stereovision
  • Sick LDMRS
• Transform tree of the rovers
• Accurate control flow

*Second element would be to provide a localization module to integrate in the chain, in order to have the full chains coming from InFuse algorithms => We propose to use the Visual Odometry from Andrea
*Third element is to provide a basic version for the DPM. We would then have the following chain of processing:

Stereovision => Disparity => DEM
||=> Visual Odometry ======= ^