An Improved Algorithm for Obstacle Avoidance by Follow the Gap Method Combined Potential Field

A novel obstacle avoidance algorithm for boat survey, “Follow the Gap Plus”, is proposed by combining the “Follow the Gap” method and adapting the “Potential Field” method with an attractive field of obstacles. Then the simulation environment for testing algorithm are generated in various situations with real-world-like environment. The results show that the proposed algorithm can go to the desired destination with better performance than “Follow the Gap” method in the environment with obstacles about 4.47% of total distance, about 7.63% of total time used, and about 54.33% of average change of direction.


Introduction
Currently robot technology have more demand for making life better.Knowledge and techniques applied to robots have more complicated as well.For example, robot movement to the designated destinations need interact with environment in different ways, such as obstacle avoidance, navigation, localization, trajectory planning etc.
In unknown environment, robot must have intelligent navigation system for planning a safety path to the goal.An algorithm for obstacle avoidance should make decision automatically with simple computation.Algorithm must find a safety path, shorter path and smooth change 1 .And when the robot found the obstacles, the algorithm must make quick decision with accuracy.For the objectives mentioned above, a novel obstacle avoidance algorithm for boat survey is proposed by focusing on the development of efficient algorithms used in shorter path and smooth change.
Most survey robots are using on the ground and in the air, whereas no robots for survey is on the water.Survey robots on water is interesting because an environment is different from the ground and have many problems, such as dynamic of the water.Therefore, the simulation of survey robot on the water is selected and developed.
The paper is organized as follows.In section 2, the related algorithms are summarized.In section 3, the proposed algorithm is presented in details.In section 4, the navigation system for testing environment are setup.In section 5, the simulation results are shown with discussion.Finally, section 6 shows the conclusions.

Artificial Potential Field Method 2-4
Artificial potential field method is based on the principle of potential field.The robot and obstacle are determined with positive value and the goal is determined with negative value.Therefore, obstacles will be pushed a robot out by created repulsive force.The goal is to attract P -613 a robot by created attractive force.So, final force on robot is the summation of all repulsive and attractive force.
This algorithm is popular implemented in mobile robot.Many researchers 3 used [SN1] this algorithm because efficiency and simplicity of mathematical model, however this algorithm has a problem in local minimum and produces a short path.

Follow the Gap Method 5
Follow the gap method avoids obstacles by finding the gap between obstacles and calculates the gap angle.Afterward, many researchers used this algorithm to implement in autonomous robot, such as autonomous car [6][7][8] or improve this algorithm by combined with others algorithm 1 for solving local minimum problem and researcher has noticed that this algorithm familiar with avoid obstacles of birds 9 .However, follow the gap method has issues about weight between gap angle and goal to find optimal ratio.

Follow the Gap Plus Method
Follow the gap method has problem when user wants the robot to avoid obstacles safely.Users need to set the weight of center gap angle with high value.The result of this makes the distance to the target increases.This proposed algorithm is intended to improve follow the gap method by using the concept of artificial potential field method applied in created repulsive force pushed out from obstacles and turned into attractive force instead.This algorithm is named with "follow the gap plus method".

Fig. 1 Concept of follow the gap plus method
Follow the gap plus method has four main step.
Step 1: calculating the gap array and finding the maximum gap.
Step 2: calculating the gap center angle using Eq. ( 1) Where and are the distance of obstacles 1 and 2 from robot respectively.∅ and ∅ are angles of obstacles respectively.∅ is the final calculated gap center angle.
Step 3: combining with attractive field and calculating distance to goal and creating attractive field to obstacle by using inverse repulsive field.Then, finding an angle between robot and obstacle using Eq. ( 2).
Determine the position of the robot changes (∆ , ∆ ) as follow 2 .
If position of robot is outside of the circle of influence, the attractive potential field is zero.Within the circle of influence but outside the radius of the obstacle, the attractive force decreases from maximum value to zero depending on distance to obstacle.The constant β > 0 is given by allowing the agent to scale in the strength of this field.Then the summation of attractive force from every obstacles is calculated in the result of angle to that position.Then, the summation of gap center angle is calculated using Eq. ( 3).∅ = ∅ ∅ (3) Step 4: calculating the final heading angle.This can be achieved by combining the gap center angle with the goal angle in Eq. ( 4).
Where minimum distance to obstacle.∅ is calculated gap combined attractive force angle.∅ goal angle.weight coefficients.

Navigation System
Autonomous survey boat requires a system for navigating to the goal.This paper proposed a simple navigation system used in survey boat experiment.The survey boat's navigation system after initial system has three main process.
First, obstacle detection process for detecting obstacle in front of the survey boat is calculated.In this P -614 process, laser scanner is used to detect obstacles.Start by checking tilt of boat, if the value is less than the threshold then the environment in front of boat begins to scan and save.Second, avoidance strategy process and a decision making of boat's heading is calculated by an obstacle avoidance algorithm, such as follow the gap method or follow the gap plus method.Third, control steering process for changing boat's heading according to the angle is calculated.
These three processes run respectively and repeat until the goal is reached.If it has other goal, system will update position of new goal and begin the first process.The Flowchart of this system is shown in Fig. 2.

Simulations and Results
The effectiveness of the proposed algorithms has been demonstrated by using the Unity3D software.In the experiments, the environment of canal with dynamic

Scenario 1: Avoiding simple obstacle
In scenario 1, considers the situation with few and easy shape obstacle.The shortest path is almost a linear path.This situation is suitable for basic testing an algorithm for usability.The results of trajectory path are shown in Fig. 3. Heading change > 15 0 0 Table .1 shows that the follow the gap plus method has better performance about 1.19 percentage of total distance, about 3.08 percentage of total time used, less heading direction change 2 times, and both algorithms have no heading change over 15 degrees.Follow the gap plus method has better performance in this scenario because an obstacle closes to the shortest path and attractive force to obstacle makes the path to close obstacle, therefore the path nearby the shortest path.While follow the gap method has only gap angle in calculation, therefore the path is far from the shortest path.

Scenario 2: Environment similar real
In scenario 2, a real-life environment is simulated in straight canal, width about 60 meters with obstructions in P -615  Table .2 shows that follow the gap plus method has better performance about 4.47 percentage of total distance, about 7.63 percentage of total time used, less heading direction change 9 times and less heading change over 15 degrees 20 times.The simulation result shows that the follow the gap plus method uses the different path from the follow the gap method.From waypoint 2 to waypoint 3, the follow the gap method uses path far from obstacle because it uses only center gap degree for decision.Whereas the follow the gap plus method used center gap degree and attractive force to obstacle, in the result the selected path is near obstacle and straight to waypoint 3.

Conclusions
The proposed algorithm, follow the gap plus method, is presented for autonomous navigation robot with the shorter and smoother path results and uses less times than follow the gap method.The simulation results show this algorithm can implement to real robot for survey on canal.However, this algorithm emphasized about shorter path, therefore robot approaching near an obstacle.So performance about short and safety path are being turned upside down.So, the future work will focus on improving the performance with safety path, testing with dynamic obstacle and testing with real robot and real environment.

Fig. 2 .
Fig.2.Navigation system flowchart water is simulated.The performance about the shorter path shown in the distance, and about smooth change shown in number of times to change heading direction and change heading angle over 15 degree.[SN3]Two[SN4] interesting scenarios are presented consisting of simple obstacles and similar real-environment[SN5].

Fig. 3
Fig. 3 Scenario 1 robot trajectory (a) Follow the gap method (b) Follow the gap plus methodTable. 1 The comparison performance of the algorithm in scenario 1. Follow the gap method Follow the gap plus method Time used (sec) 37.70 36.53Distance (m) 254.42 251.38 Heading direction change 39 37 the canal.No dynamic obstacle is consider in the experiment.The result of trajectory path is shown in Fig.4.(a) (b) Fig. 4 scenario 2 robot trajectory (a) Follow the gap method (b) Follow the gap plus method

Table . 2
The comparison performance of the algorithm in scenario 2.