Control System For Autonomous Navigation Research Articles

Experimental Verification of a Control System for Autonomous Navigation

A flexible architecture is developed with the purpose of supporting education and research on the field of autonomous vehicles. A pure electric vehicle is equipped with on-board computational units, sensors and actuator interfaces. This paper presents the current status of the control system and its validation by means of navigation experiments. With the cascade control architecture, problems of actuator dead-zone, sensor offset errors, path tracking and redesign for obstacle avoidance are addressed.

Ultra-wideband pose detection method based on TDOA positioning model for boom-type roadheader

In deep and dangerous coal seam tunnelling, the autonomous navigation control system (ANCS) of the boom-type roadheader is the core that realises unattended work. The remote pose detection of the boom-type roadheader is the key task of the ANCS. In this study, an ultra-wide band (UWB) pose detection system (UPDS) for boom-type roadheaders is designed which realises the remote measurement of position and attitude parameters (heading, roll, and pitch angles) of the boom-type roadheader in a narrow and long enclosed roadway space. Based on the time difference-of-arrival (TDOA) positioning model, three UPDS positioning algorithms are proposed: Indirect positioning algorithm (IPA-D), Taylor series expansion algorithm (Taylor-D), and Chan positioning algorithm (Chan-D). A complete calculation process is deduced from the three UDPS positioning algorithms. Their accuracies are analysed based on the measured data of a P440 UWB ranging module in a narrow and long roadway. The positioning accuracy of IPA-D behaves better than those of Taylor-D and Chan-D: Within 95 m of the roadway, IPA-D can achieve values at a centimetre scale and the positioning error increases with increasing measurement distance. The calculated UPDS attitude angle error based on IPA-D increases with increasing measurement distance of up to 95 m; The roll angle error is approximately 0.05°, and the pitch and heading angles are approximately 0.15°. The presented UPDS meets the accuracy requirements for the pose detection of boom-type roadheaders in a fully mechanised excavation face and provides a reliable theoretical basis for ANCSs of boom-type roadheaders.

Fuzzy Control System for Autonomous Navigation of Thymio II Mobile Robots

This paper treats the autonomous navigation problem of robotic systems in a dynamic and uncertain environment. In particular, we are interested in determining the robot motion to reach the target while ensuring their own safety and that of different agents that surround it. To achieve these goals, we have adopted a fuzzy controller for navigation and avoidance obstacle, taking into account the changing nature of the environment. The approach has been tested and validated on a ThymioII robots set. As application field, we have chosen a parking problem..

Fuzzy Control System for Autonomous Navigation and Parking of Thymio II Mobile Robots

This paper proposed a fuzzy controller for the autonomous navigation problem of robotic systems in a dynamic and uncertain environment. In particular, we are interested in determining the robot motion to reach the target while ensuring their own safety and that of different agents that surround it. To achieve these goals, we have adopted a fuzzy controller for navigation and avoidance obstacle, taking into account the changing nature of the environment. The approach has been tested and validated on a Thymio II robots set. As application field, we have chosen a parking problem.

A Characterization of the Utility of Using Artificial Intelligence to Test Two Artificial Intelligence Systems

An artificial intelligence system, designed for operations in a real-world environment faces a nearly infinite set of possible performance scenarios. Designers and developers, thus, face the challenge of validating proper performance across both foreseen and unforeseen conditions, particularly when the artificial intelligence is controlling a robot that will be operating in close proximity, or may represent a danger, to humans. While the manual creation of test cases allows limited testing (perhaps ensuring that a set of foreseeable conditions trigger an appropriate response), this may be insufficient to fully characterize and validate safe system performance. An approach to validating the performance of an artificial intelligence system using a simple artificial intelligence test case producer (AITCP) is presented. The AITCP allows the creation and simulation of prospective operating scenarios at a rate far exceeding that possible by human testers. Four scenarios for testing an autonomous navigation control system are presented: single actor in two-dimensional space, multiple actors in two-dimensional space, single actor in three-dimensional space, and multiple actors in three-dimensional space. The utility of using the AITCP is compared to that of human testers in each of these scenarios.

A Vision-Based Guidance System for UAV Navigation and Safe Landing using Natural Landmarks

In this paper a vision-based approach for guidance and safe landing of an Unmanned Aerial Vehicle (UAV) is proposed. The UAV is required to navigate from an initial to a final position in a partially known environment. The guidance system allows a remote user to define target areas from a high resolution aerial or satellite image to determine either the waypoints of the navigation trajectory or the landing area. A feature-based image-matching algorithm finds the natural landmarks and gives feedbacks to an onboard, hierarchical, behaviour-based control system for autonomous navigation and landing. Two algorithms for safe landing area detection are also proposed, based on a feature optical flow analysis. The main novelty is in the vision-based architecture, extensively tested on a helicopter, which, in particular, does not require any artificial landmark (e.g., helipad). Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations.

A micro-rover navigation and control system for autonomous planetary exploration

This paper describes an end-to-end control system for autonomous navigation of a small vehicle at a remote place, e.g. in space for planetary exploration. Due to a realistic background of this study the proposed method has to deal with limited knowledge about the environment as well as limited system resources and operational boundary conditions, especially a very large time delay in the communication between the ground control station and the space segment. To overcome these constraints the remote system has to act in a very autonomous way. Ground support minimizes the computational load of the remote system. High-level information interchange reduces the communication bandwidth requirements.

自律走行式床面清掃ロボットの開発

This paper describes a new mechanism of a floor cleaning robot and its control system for autonomous navigation. The robot can be equipped with a cleaning function; scrubbing or sweeping. The controller memorizes the positions of obstacles by repeating longitudinal traverse and swivel 90 [deg] motion. The robot moves to the back of the obstacles and cleans up all area using this information.