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Image Roombots

Roombots

Modular robotics for adaptive and self-organizing furniture that moves, self-assembles, and self-reconfigures. Our dream is to provide multi-functional modules that are merged with the furniture and that lay users and engineers can combine for multiple applications.

Key features:
  • Off-grid (free) and on-grid locomotion
  • Position, speed or Central-Pattern-Generator (CPG) control
  • One module can lift another module and up to 500 g as payload in the end effector
  • Extensible with specialized elements (Universal Gripper, LED spotlight, camera + on-board PC)
  • 2 LED rings per module for visual feedback
  • Local sensors to detect docking position
  • 10 connection surfaces per module
  • 3 degrees of freedom and 2 active connection mechanisms per module
  • Controlled from centralized PC; commands over serial port on Bluetooth
  • Easy-to-use GUI (based on Unity; only visualization, no physics)
Possible applications:
  • Novel interface to control and coordinate multiple modules at the same time
  • Smart moving manipulator or spotlight
  • Automatic construction of shapes or objects
  • Rapid prototyping of robots by coordinating multiple modules

Access information

Corresponding infrastructureÉcole Polytechnique Fédérale de Lausanne
BioRobotics Lab
LocationRoute Cantonale, 1015 Lausanne, Switzerland
Unit of accessWorking day

Technical specifications

Outer gearboxes reduction:305:1 (custom made)
Inner motor:Maxon RE-max 24
Outer motors:Maxon RE 25
Communication:Bluetooth
Energy source:4-cell LiPo battery, 1200 mAh. Autonomy ~1 hour
Active connection type:4-way symmetrical gender-less mechanical latches
Number of connection surfaces:10 (active or passive)
Degrees of freedom:3 (continuous rotational)
Weight:1.7 kg (3.1 lb)
Overall dimensions:110x110x220 mm (4.3?x4.3?x8.7?)
Inner gearbox reduction:366:1 (custom made)
Outer dofs specs:31.5 RPM (no load), 8.4 Nm (nominal)
Inner dof specs:20.4 RPM (no load), 4.3 Nm (nominal)

Additional information

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730994

Training
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