Workshop (sadna)
Spring 2022, 0368-3535-01
Lecture: Wednesday, 14:00-16:00 , Dan David 205
Instructor: Dan Halperin, [email protected]
Office hours by appointment
Teaching assistant: Dror Livnat ([email protected])
Software helpdesk: Michael Bilevich (michaelmoshe at mail tau ac il)
Projects: Following are a few projects. More details about all the projects, including video clips, appear in the table further below.
General information: Motion planning algorithms compute collision-free motion paths for objects that move among obstacles. They arise in robotics, graphical animation, surgical planning, navigation systems, computational biology and computer games, among other domains. In this workshop we will explore and apply algorithms for one of several robot systems. For example: (i) a fleet of blue robots that need to collect items in an environment cluttered with obstacles, while avoiding a fleet of red robots; (ii) two robot arms that need to carry out a joint task; (iii) drones that need to carry out a prescribed task while avoiding obstacles on their way as well as other drones.
A typical project involves implementing motion planning algorithms for a robotic arm, an autonomous boat, a drone, or a Roomba like robot in simulation environment, or alternatively, implementing a similar task with physical robots.
Class meetings
At the beginning of the workshop, the very basics of motion planning algorithms will be presented, and possible projects will be laid out. Below is the complete list of expected class meetings.
- 23/2/22 – Introduction to robot motion planning + suggested projects
- 2/3/22 – More background, review of software tools
- 30/3/22 – Presentation of project plan
- 1/6/22 – Presentation of POC (Location: Checkpoint building, room 380)
- 7/9/22 – Presentation of the final project (Location: Checkpoint building, room 420)
References
- Sampling Based Robot Motion Planning, Oren Salzman ,Communications of the ACM, October 2019
- Sampling Based Robot Motion Planning: A Review, Elbanhawi and Simic ,IEEE Access, 2014 (free online)
- A Little More, a Lot Better: Improving Path Quality by a Path Merging Algorithm, B. Raveh, A. Enosh and D. Halperin,
IEEE Transactions on Robotics, 27(2): 365-371, 2011
Teamwork: The project is intended to involve a significant amount of teamwork. The recommended team size is three. Each team will choose a project among the list of projects, and submit the final project later in the summer.
Teams and Projects
Project | Members | Description + Demonstration (click to view) |
---|---|---|
Dual Driving & Discovering Networks | Roy Dvir Daniel | Detecting obstacles and planning the movement accordingly |
CoMotion | Shai Alon Tomer |
Simulations of a player in the CoMotoin game |
Self Localization in a Known Environment of a Physical Robot | Alon Uri |
Estimating the location of a Robomaster robotic vehicle based on distance measurements in a know environment |
Waste Sorting | Nir Z. Shir Omer |
Sorting different kinds of waste |
Motion Planning of a Robotic Vehicle | Anastasia Daniel |
Planning the motion of a robotic vehicle chasing a moving target in a known environment under physical constraints (e.g., maximum speed, maximum acceleration, minimum rotation angle) in minimum time |
“Don’t Drop the Package” Autonomous Forklift Using a Physical Robot | Avigail Inbar Guy |
Passing cargo in a known environment with obstacles as fast as possible without dropping it with a Robomaster robotic vehicle |
Motion Planning of a Physical Robotic Arm | Eyal Harel Jonathan |
Planning the motion of the Kinova arm to translate lesson plans into drawing on a board |
FlyBall | Efrat Ori Maya Nir G. |
Bouncing a ball using two drowns that play in turns, keeping the ball in the air |
Past workshop projects:
Paranoid Android | Drone project: | iRobot project: |
Robotic boat | RoBoat project |
Related projects to stimulate ideas (not from the workshop):