Cube Swarm
Gripper Mechanism
For my undergraduate capstone project, I collaborated with 6 other people to develop a swarm robotic system using interlocking cube robots to cross gaps for search and rescue applications. This project serves as a proof of concept for the use of swarm robotics in a search and rescue environment. The swarm uses a differential drive system and communicates with a centralized Bluetooth communication network. They're capable of locking together with a custom mechanical gripper and bridging a gap that's too big for individual robots.
Subassembly View
I was in charge of the navigation system. The swarm uses the Extended Kalman Filter (EKF) as the sensor fusion algorithm to localize itself in the environment. Encoder readings are used to get a baseline prediction of the robot's positions. AprilTags are placed on every side of each robot and on landmarks around the environment. The robots use the onboard Arducam for AprilTags detection and position correction to prevent error accumulation.
To avoid collisions, the swarm uses Conflict-based Search (CBS) on a centralized computer as the multi-agent path planning algorithm. CBS uses a set of constrained, single-agent pathfinding problems to find paths that are consistent with these constraints. At the low level, the algorithm uses A* with an additional timestep component for individual robot path planning. To demonstrate the navigation system, I made a Gazebo simulation with simplified URDF models of the robots as seen below. The simulation initializes the cubes at random locations and has them line up without collisions, attach, and cross a gap.
Gazebo Simulation
Locking Demo
