Curved Trajectory Detection : A Novel Neurocognitive Perception Approach for Autonomous Smart Robots

TL;DR

This paper introduces a new neuronal circuit for autonomous robots that detects curved object movements, enhancing their perception and interaction capabilities with dynamic environments.

Contribution

A novel modular neuronal circuit model for curved trajectory detection in autonomous robots, with robustness against epileptic-like disturbances and applicability to straight movements.

Findings

Effective detection of curved and straight movements in simulations.

Robust performance against epileptic seizure-like activity.

Successful implementation on a Braitenberg vehicle for empirical validation.

Abstract

Braitenberg vehicles could be mentioned as the seminal elements for cognitive studies in robotics fields especially neurorobotics to invent more smart robots. Motion detection of dynamic objects could be taken as one of the most inspiring abilities into account which can lead to evolve more intelligent Braitenberg vehicles. In this paper, a new neuronal circuit is established in order to detect curved movements of the objects wandering around Braitenberg vehicles. Modular structure of the novel circuit provides the opportunity to expand the model into huge sensory-biosystems. Furthermore, robust performance of the circuit against epileptic seizures is beholden to simultaneous utilization of excitatory and inhibitory stimuli in the circuit construction. Also, straight movements, as special case of curved movements could be tracked. PIONEER, with due attention to its suitable neurosensors, is used as a Braitenberg vehicle for empirical evaluations. Simulated results and practical experiments are applied to this vehicle in order to verify new achievements of the curved trajectory detector.