Robots Navigate Tight Spaces Using Contradiction Logic

As autonomous robots become increasingly common in factories, warehouses, and other confined spaces, their ability to navigate narrow corridors without collisions remains a critical challenge. A new approach using paraconsistent annotated evidential logic offers a solution by allowing robots to process conflicting sensor information more effectively, potentially improving safety and efficiency in automated transportation systems.

The research team developed an algorithm that enables terrestrial mobile robots to navigate corridors while maintaining manufacturer specifications for motor performance. The system processes contradictory evidence from multiple sensors to make navigation decisions, rather than requiring consistent data inputs. This approach helps robots continue functioning effectively even when sensor readings conflict or provide incomplete information.

The methodology involved four distinct phases. First, researchers conducted literature reviews on servomotors, microcontrollers, and paraconsistent annotated logic. They then created models for terrestrial mobile robot control using mechatronic systems technology. Programming was developed in C language specifically for microcontroller implementation, with tests performed using an oscilloscope to monitor microcontroller signals and observe motor movement. The paraconsistent annotated logic was integrated into the decision-making process to verify its utility in directional control.

The robot design incorporated six ultrasonic sensors connected to a microcontroller through signal processing for directional control. Practical tests showed the system could maintain servo motor operation within required specifications, with pulse widths of 2.040ms for 180-degree angles and 1.020ms for smaller movements matching manufacturer requirements. The paraconsistent logic implementation allowed the robot to handle various logical states including true, false, paracompleteness, and inconsistent states, adjusting movement accordingly based on degrees of certainty and uncertainty calculated from sensor evidence.

This approach matters for real-world applications because it addresses a fundamental limitation in autonomous navigation: the frequent occurrence of conflicting or uncertain sensor data in complex environments. In factory settings, where robots transport components along assembly lines, or in domestic applications like cleaning robots, the ability to navigate safely despite sensor contradictions could reduce maintenance needs and improve operational reliability. The method contributes to longer motor life cycles by maintaining manufacturer specifications during displacement operations.

The research acknowledges limitations in the current implementation, noting that complete paraconsistent logic implementation requires further development to ensure all specifications are maintained. Future work must improve the system to guarantee specific performance standards while exploring additional possibilities for experimentation with the approach.