An Improved Algorithm for Collision Avoidance in
Environments Having U and H Shaped Obstacles
Muhammad ZOHAIB1, Syed Mustafa PASHA1,
Nadeem JAVAID1, Abdus SALAAM2, Jamshed IQBAL1
1 COMSATS Institute of Information Technology (CIIT)
2 Iqra National University,
Abstract: This paper proposes a novel obstacle avoidance algorithm for autonomous mobile robot control. The proposed approach brings a solution to the problem of robot traversal in critical shaped environments and offers several advantages compared to the reported approaches. The algorithmic approach, named as, Intelligent Follow the Gap Method (IFGM) is based on improved Intelligent Bug Algorithm (IBA) and Follow the Gap Method (FGM). The robot field of view is taken into consideration. The IBA avoids obstacles by following their edge and scanning the path to destination, thus making the approach goal-oriented avoiding local minimum problem. To characterize the performance of IFGM, various scenarios of obstacles are considered. These scenarios range from having obstacles defined by simple and symmetrical shapes to critical shaped obstacles. The simulation results demonstrate that the algorithm results in safer and smoother trajectories in the presence of obstacles. It offers fast convergence and does not suffer from local minima. Finally, the performance comparison of the proposed algorithm with that of the reported approaches in terms of distance-time plots confirms the efficacy of the presented approach. The proposed algorithm lends itself to future implementations in the navigation of mobile and industrial robots, especially in applications exhibiting crucial time and critical obstacles including disaster management, spy, elderly people assistance and soccer games.
Keywords: Obstacle avoidance, Path planning, Autonomous control, Safe navigation, Mobile robot.
CITE THIS PAPER AS:
Muhammad ZOHAIB, Syed Mustafa PASHA, Nadeem JAVAID, Abdus SALAAM, Jamshed IQBAL, An Improved Algorithm for Collision Avoidance in Environments Having U and H Shaped Obstacles, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (1), pp. 97-106, 2014.
Recent technological advancements have made it possible to see the ‘fiction’ robots in reality in various spheres of life ranging from articulated robots  to mobile robots . Most applications demand a robot to be mobile. This has brought up serious issues regarding mobile robot interaction with the environment, including obstacle avoidance, navigation, localization, path planning etc. [3,4].
In a completely known environment, it is easy to implement the robot control, by simply creating a map and applying A* search algorithm to generate a reference path. On the other hand, a partially or completely unknown environment demands intelligence in robot navigation as pointed by Brassai et al. in . Planning a safe trajectory for a mobile robot is achieved with an intelligent algorithm that uses knowledge of goal position and the sensorial information of the surrounding environment. Such an algorithm for obstacle avoidance permits autonomy in operation and preferably has low computational complexity. The algorithm should feature a safer, shorter and smoother trajectory while ensuring obstacle avoidance. The algorithm should be able to take a quick decision while encountering an obstacle and should let the robot to traverse in an environment having diverse shaped obstacles ranging from simple to critical.
With these features as primary objectives, the present research proposes a novel obstacle avoidance algorithm aimed at improving the intelligence level of the reported strategies.
The proposed algorithms have capability to take self decisions even while encountering critical shaped obstacles in a way similar to humans’ problem-solving approach. The algorithms can permit a robot to follow a smoother, shorter and safer trajectory as compared to the existing methodologies. Moreover, reasonable computational requirements of the proposed algorithms simplify the physical implementation in real control applications.
The paper is organized as follows. Section 2 reviews state-of-the-art of reported algorithms for collision avoidance. Section 3 claims on novelty of the proposed algorithm detailed in Section 4. Section 5 presents simulations results to validate the proposed approach. Finally Section 6 comments on conclusions.
- IQBAL, J., R. ISLAM, H. KHAN, Modeling and Analysis of a 6 DOF Robotic Arm Manipulator, Canadian Journal on Electrical and Electronics Engineering, vol. 3(6), 2012, pp. 300-306.
- IQBAL, J., R. NABI, A. A. KHAN, H. KHAN, A Novel Track-Drive Mobile Robotic Framework for Conducting Projects on Robotics and Control Systems. Life Science Journal, ISSN 1097-8135, vol. 10(3), 2013, pp.130-137.
- KAREEM JARADAT, M. A., M. AL-ROUSAN, L. QUADAN, Reinforcement Based Mobile Robot Navigation in Dynamic Environment, Robotics and Computer-Integrated Manufacturing, vol. 27, no. 1, 2011, pp. 135-149.
- CARRETERO, J. A., I. EBRAHIMI, R. BOUDREAU, Overall Motion Planning for Kinematically Redundant Parallel Manipulators, Journal of Mechanisms and Robotics, vol. 4, no. 2, 2012
- BRASSAI, S. T., B. IANTOVICS, C. ENACHESCU, Optimization of Robotic Mobile Agent Navigation, Studies in Informatics and Control, ISSN 1220-1766, vol. 21(4), 2012, pp. 403-412.
- BABINEC, A., M. DEKAN, F. DUCHOŇ, A. VITKO, Modifications of VFH Navigation Methods for Mobile Robots, Procedia Engineering, vol. 48, 2012, pp. 10-14.
- SEZER, V., M. GOKASAN, A Novel Obstacle Avoidance Algorithm: Follow the Gap Method, Robotics and Autonomous Systems, vol. 60, no. 9, 2012, pp. 1123-1134.
- ZOHAIB, M., M. PASHA, R. A. RIAZ, N. JAVAID, M. ILAHI, R. D. KHAN, Control Strategies for Mobile Robot with Obstacle Avoidance, Journal of Basic and Applied Scientific Research, ISSN 2090-4304, vol. 3 no. 4, 2013, pp.1027-1036.
- ZHU, Y., T. ZHANG, J. SONG, X. LI, A New Hybrid Navigation Algorithm for Mobile Robots in Environments with Incomplete Knowledge, Knowledge-Based Systems vol. 27, 2012, pp. 302-313.
- SGORBISSA, A., R. ZACCARIA, Planning and Obstacle Avoidance in Mobile Robotics, Robotics and Autonomous Systems, vol. 60, no. 4, 2012, pp. 628-638.
- QUINLAN, S., O. KHATIB, Elastic Bands: Connecting Path Planning and Control, IEEE International Conference on Robotics and Automation (ICRA), 1993, pp. 802-807.
- SUSNEA, I., A. FILIPESCU, G. VASILIU, G. COMAN, A. RADASCHIN, The Bubble Rebound Obstacle Avoidance Algorithm for Mobile Robots, 8th IEEE Intl. Conference on Control and Automation, 2010, pp. 540-545.
- PHILIPPSEN, R., R. SIEGWART, Smooth and Efficient Obstacle Avoidance for a Tour Guide Robot, International Conference on Robotics and Automation (ICRA), 2003, pp. 446-451.
- ZHU, Y., T. ZHANG, J. SONG, X. LI, A New Bug-type Navigation Algorithm Considering Practical Implementation Issues for Mobile Robots, IEEE International Conference on Robotics and Biomimetics, 2010, pp. 531-536.
- YUFKA, A., O. PARLAKTUNA, Performance Comparison of Bug Algorithms for Mobile Robots, Proceedings of the 5th International Advanced Technologies Symposium, Turkey. 2009.