Hardware Schemes for Autonomous Navigation of Cooperative-type Multi-robot in Indoor Environment

J. Inst. Eng. India Ser. B https://doi.org/10.1007/s40031-021-00659-6 ORIGINAL CONTRIBUTION Hardware Schemes for Autonomous Navigation of Cooperative-type Multi-robot in Indoor Environment G. Divya Vani1,2 • Srinivasa Rao Karumuri1 • M. C. Chinnaiah2 Received: 16 September 2020 / Accepted: 28 July 2021  The Institution of Engineers (India) 2021 Abstract This study proposes about the autonomous navigation of a multi-robot for transportation in indoor environments. This transportation is integrated with three foldings of VLSI architectures; they are 1) shortest optimal path planning 2) behavioral control between multi-robot with leadership swapping methods as per dynamic conditions and 3) obstacle avoidance by multi-robot. The hardware schemes have been designed for navigation of multirobot with shortest path planning, based on an extended Dijkstra algorithm along with the Delaunay triangulation method. The behavioral control mechanism between the multi-robot is another challenge at the time of navigation and obstacle avoidance at both static and dynamic conditions in real-time scenario. The leader and follower approaches are deployed for cooperation between multirobot to accomplish the task. The VLSI architectures are proposed for multi-robot navigation in the warehouse-type indoor environment. It is developed using Verilog HDL, simulated and synthesized with Xilinx Vivado 17.1. The Zynq-7000 SoC ZC702 FPGA is used as the target device. Keywords FPGA  Multi-robot  Behavioral control  Dijkstra algorithm  Obstacle avoidance & Srinivasa Rao Karumuri 1 Department of Electronics & Communication Engineering, K L University, Guntur, Andhra Pradesh, India 2 Department of Electronics & Communication Engineering, B V Raju Institute of Technology, Narsapur, Medak, Telangana, India Introduction An extensive study has been conducted on autonomous service-based robot navigation in indoor environments. The indoor-based service robots are differentiated as per environment such as industry, home applications, hospital and cafeteria/hotel. In COVID-19 pandemic, the importance of service robot has been recognized for social services. The warehouses and industries are also integrated with robots for carrying the products. The challenges of individual robots at the warehouse are carrying products with outbound due to bigger sizes than the basement of the robot, where it creates a chance for collision and cross docking at the environment. In this regard, individual robots can carry products when the product size is less than the robot basement size. Cranes can be used for carrying huge products, but they cannot be opted for the medium sized products due to space issues. It is one of the major challenges in warehouses and industrial environment. This paper provides solutions using cooperative-type multi-robot for carrying medium-sized products. In this context, the collaboration of multi-robot with the cooperative-type formation plays a vital role. This cooperative mechanism impacts the multi-robot to traverse with the behavioral control among them to defined destination nodes. The research towards shortest path planning has been protracted in the robotic field from few decades, which is essential to accomplish the robotic navigation. Most of the navigational algorithms have been developed based on grid map and graph theory. The Dijkstra algorithm is one of the familiar shortest path planning algorithms, and it is widely used for 2D mobile robot navigation. Edsger Wybe Dijkstra is a Dutch scientist, expert in the computer field; he proposed shortest path planning as a Dijkstra’s algorithm. 123 J. Inst. Eng. India Ser. B In the recent years, the algorithm is modified with various aspects as per real-time scenario; the authors K. Wei et al. [1] represented about how a maximum load path problem can be dissolved with modified Dijkstra’s algorithm. Similarly, the same algorithm has been used for optimal path and other applications like parking of robots [2]. The authors Dong Guo et al. [3] has mentioned about emissions effect while driving and also about fuel consumption by using the shortest path method. The automatic guided vehicle transmission in an environment with the grid method using Dijkstra algorithm was represented by Zheng Zhang et al. [4]. The team of authors Deepak Gautam et al. [5] discussed regarding Dijkstra-based shortest path for quad rotor helicopter movement. Sai Shao et al. [6] mentioned about the importance of shortest path in light-sport aircraft transmit. The authors M. Luo et al. [7, 8] have discussed regarding the extended version of the Dijkstra algorithm for optimal path planning. Thus, path planning is highly indeed in an industrial environment for material transportation. In the existing system, at warehouse and industries the products are carried out by individual autonomous robot and they are not capable of carrying the medium-sized products. In this aspect, the multi-robot-based transportation methods are essential to carry medium-sized products using collaboration methods. The collaboration of motion robots like PUMA 560 arms for carrying payload was presented by H. Bai et.al [9]. In similar lines, bio-inspired methods like coalition formation of multi-robot to execute gaming theory of robotics is mentioned by authors X. Liang et al. [10]. One of the robot formations with queue structure was developed by authors C. Fua et al. [11]. The authors Y. Kim et al. [12] investigated about formation of multi-robot with localization strategy. The behavioral control between robots is another aspect of multi-robot formation. The cooperative control methods for vehicle formation have been developed by W.Ren et al. [13]. The other researchers G. Antonelli et al. [14] mentioned about control algorithms of null-space-based behavioral (NSB). The researchers have contributed control mechanism with fuzzy methods by authors J. Huang et al. [15], and multi-robot control with adaptive methods was discussed by J. Fan et al. [16]. The leader follower approaches are one of the best methods in the cooperative formation of multi-robot. The leader follower method for mobile vehicle was described by Shao et al. [17]. V. Kumar et al. [18] have mentioned regarding obstacle avoidance using Gaussian algorithms with a heuristic approach for leader follower formation control. The obstacle avoidance can be performed by a multirobot with two approaches: 1. distributive formation behavior control and 2. centralization formation behavior 123 control. Among these, centralized approach is an appropriate method used in the flock group for transportation of products. The single-robot obstacle avoidance is mentioned with various control methods such as bug, vbug, bug2, voronoi diagram and graph theory. The key aspect of centralized multi-robot approach is leadership, and it plays a vital role in the execution of the multi-robot transportation with obstacle avoidance. In this context, a (...truncated)