sepp

small size evaluation and prototyping platform - yet another autonomous RC car

See SEPP on a first teleoperation rideout here: https://youtu.be/caKfN4w3eOs

See SEPP blink and with new bumpers: https://youtu.be/2P67onShV-0

More impressions here: https://github.com/intence/sepp/wiki/Impressions

Read the SEPP wiki, if you want to see more about architecture and development with SEPP: https://github.com/intence/sepp/wiki

Goals

• Create a platform to evaluate sensors, sensor fusion approaches and algorithms in a small sized and comparatively cheap prototype
• Use open source hardware and software to enable contributors and users to clone the prototype
• Use computer vision and ultrasonic sensors to implement first autonomous functions
• Use artificial intelligence for trained autonomous functions
• Use the platform to collect data for training of artificial intelligence

Used technologies (or planned)

• 1:10 remote controlled car set with new motor (crawler brushed motor), new steering servo and stiffer
• nvidia jetson tx1 - GPU computing platform for hosting ROS and computer vision algorithms and machine learning
• Arduino - one to have a sensor board and one to have a actuator board
• ros - Robot Operating System (ROS)
• OpenCV - Open Source Computer Vision Library
• TensorFlow - open source machine learning framework [planned]
• sensors: 8 x ultra sonic, rgb camera, 3D camera (kinect style), gyroscope, radar, gps dongle, 2D 360 degrees LiDAR
• actuators: thrust servo, steering servo, red flashlight, buzzer
• infrastructure: ethernet shields for arduino, ethernet switch, NiMh accu pack, usb hubs, power bank (to power arduinos an jetson tx1)
• car body: bumpers, constructed aluminium frame designed and made by Andreas N. aka G-Shocker (thanks for that!), constructed 3D printed parts (https://www.thingiverse.com/thing:3105985), plenty of tape, cable ties, jumper cable and solder :)

Skills of sepp today

• jetson tx1 up and running on ubuntu Xenial
• ROS Lunar Loggerhead up and running on jetson tx1
• simple computer vision pipeline implemented as ROS nodes with openCV
• ultrasonic sensors are read by sensor board (arduino) and sent to ROS core on jetson by ethernet
• thrust and steering servos are controlled by actuator board (arduino) over ethernet messages sent by a ROS node on jetson tx1
• ROS can be run in a distributed setup, so ROS nodes on a remote PC can register on the ROS core on sepp´s jetson tx1
  • debugging and logging of ros messages is possible on a remote machine
  • visualizations of the camera streams and input and output signals are possible on a remote machine
• teleoperation is implemented in a simple manner
  • video streams of rgb camera (backwards) and 3D camera (to the front) ist sent to ROS core on jetson tx1 over Wifi
  • a ROS node which reads joystick input on a remote pc sends steering information to actuator board which controls the servos
  • a simple collition detection is implemented which reads ultrasonic signals and triggers a ermergancy stop if an obstacle is coming in the way of sepp

As you can see the real autonomous functions have to be implemented. Some work has to be done ;)

Possible next steps

• activate buzzer while driving, so nobody falls over sepp
• implement a mode manager for all modes sepp can be in
• try to think about an architecture of ROS nodes to implement sensor fusion, steering of the car and autonomous functions
• think about debugging in ROS nodes running on the jetson tx1
• simple lane depature warning done by computer vision -> can be extended to lane follow function
• do a "trained drive" on a known parkour: train TensorFlow with data of humans driving the parkour

more to follow...