Biologically Inspired Modular Neural Control for a Leg-Wheel Hybrid Robot

Poramate Manoonpong, Florentin Wörgötter, Pudit Laksanacharoen

Research output: Contribution to journalJournal articleResearchpeer-review


In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot’s specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.
Original languageEnglish
JournalAdvances in Robotics Research : An International Journal
Issue number1
Pages (from-to)101-126
Number of pages25
Publication statusPublished - 2014


  • neural networks
  • mobile robot control
  • reactive behavior
  • obstacle avoidance
  • autonomous robots


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