Speed Optimization Control for Wheeled Robot Navigation with Obstacle Avoidance Based on Viability Theory

Abstract

Original scientific paperThe navigation efficiency of wheeled robots needs to be further improved. Although related research has proposed various approaches, most of them describe the relationship between the robot and the obstacle roughly. Viability theory concerns the dynamic adaptation of evolutionary systems to the environment. Based on viability, we explore a method that involves robot dynamic model, environmental constraints and navigation control. The method can raise the efficiency of the navigation. We treat the environment as line segments to reduce the computational difficulty for building the viability condition constraints. Although there exists lots of control values which can be used to drive the robot safely to the goal, it is necessary to build an optimization model to select a more efficient control value for the navigation. Our simulation shows that viability theory can precisely describe the link between robotic dynamics and the obstacle, and thus can help the robot to achieve radical high speed navigation in an unknown environment.Key words: Wheeled robot, Navigation, Obstacle avoidance, ViabilityOptimizacija upravljanja brzinom mobilnog robota s izbjegavanjem prepreka zasnovana na teoriji vijabilnosti. Postoji potreba za unaprije enjem učinkovitosti navigacije mobilnih robota. Iako su vezana istraži-vanja predložila različite pristupe, većina ne opisuje precizno odnos izme u robota i prepreke. Teorija vijabilnosti istražuje dinamičke adaptacije evolucijskih sustava njihovoj okolini. Učlanku istražujemo metodu koja može povećati učinkovitost navigacije, zasnovanu na vijabilnosti koja uključuje dinamički model robota, ograničenja okoline robota i samu navigaciju. Radna okolina predstavljena je ravnim crtama kako bi se smanjila računska složenost izgradnje ograničenja. Iako postoji veliki broj iznosa upravljačkih veličina koje bi sigurno uputile robota prema cilju, potrebno je izraditi optimizacijski model koji bi odabrao učinkovitiju upravljačku vrijednost za navigaciju. Izvedene simulacije pokazuju da teorija vijabilnosti može precizno opisati vezu izme u prepreke i dinamike robota te na taj način pomoći robotu da postigne radikalno veće brzine pri navigaciji u nepoznatim prostorima.

Optimization of Dynamic Obstacle Avoidance Path of Multirotor UAV Based on Ant Colony Algorithm

“…Since UAVs themselves lack the ability to perceive the environment, in order to ensure the UAV's understanding and grasp of the environment, it is necessary to enable the UAV to acquire information including the obstacles in the surrounding environment, other actions exhibited by the obstacles, nonobstacle areas that the UAV can pass through, and flexible actions. The technique to obtain this information by fusing data from multiple sensors such as LIDAR, cameras, and millimeter wave radar is the environmental sensing technique [10].…”

Determining the Viability of an Unbounded Polyhedron for a Switched System

“…Te research on viability focuses on continuous evolution of a dynamic system within a constraint region, aiming to maintain the system state within the constraint region by describing the possible trajectories and trying to select appropriate control, which provides essential guarantee for the safe and continuous evolution of the system, making the study of viability theory of great importance. Viability theory has brought a new research approach to the safe evolution of dynamic systems, and it has now been applied to fshery ecosystems [2], renewable energy systems [3,4], robot control [5,6], and system fault detection [7].…”

The computation of the viability kernel for switched systems

“…The problem of viability [1] concerns the dynamic evolutions governed by complex systems under uncertainty that are found in many domains involving living beings, from biological evolution to economics [2], from environmental sciences to financial markets [3,4], from control theory to cognitive sciences [5][6][7]. It aims at controlling dynamical systems with the goal to maintain the state of the systems inside a given set which we called the constraint set or safe region.…”