Li-Ren Li

Bio: Li-Ren Li is an academic researcher from Chang Gung University. The author has contributed to research in topics: Algorithm design & Communications protocol. The author has an hindex of 1, co-authored 1 publications receiving 24 citations.

Path planning protocol for collaborative multi-robot systems

Abstract: Wireless ad hoc sensor networks are being developed to collect data across the area of deployment. These technologies enable multiple robots to form a temporary multi-robot team and cooperate with each other to launch a complex mission. A path planning algorithm and well-organized communication protocol are needed when the multi-robot systems have to search for or reach a designate target. It is more complex in designing a collaborative path planning algorithm and communication protocols for multi-robot systems since it has to consider avoiding intra-team collisions, energy efficiency, information sharing and cooperation problems, etc. Moreover, unlike single robot path planning problem, a multi-robot system is usually constructed by several simple, cheap, function-restricted, and energy-limited robots to plan a path toward the target by cooperative fashion. This is the main advantage of the puny multi-robot system. Therefore, in this paper, we propose a simple but efficient collaborative path planning algorithm (CPPA) and a communication protocol for the sensor multi-robot systems where the energy consumption is reduced as well as the duration of reaching the goal is shortened. Moreover, considering the survivability of the mission, the proposed algorithm can enable the sensor robots to complete the mission even if some robots are failed by accidents. Experiment results show that the energy consumption and computation of proposed algorithm is lower than the multiple independent robots or other methods.

Simulation and field testing of multiple vehicles collision avoidance algorithms

Abstract: A global planning algorithm for intelligent vehicles is designed based on the A* algorithm, which provides intelligent vehicles with a global path towards their destinations. A distributed real-time multiple vehicle collision avoidance ( MVCA ) algorithm is proposed by extending the reciprocal n-body collision avoidance method. MVCA enables the intelligent vehicles to choose their destinations and control inputs independently, without needing to negotiate with each other or with the coordinator. Compared to the centralized trajectory-planning algorithm, MVCA reduces computation costs and greatly improves the robustness of the system. Because the destination of each intelligent vehicle can be regarded as private, which can be protected by MVCA, at the same time MVCA can provide a real-time trajectory planning for intelligent vehicles. Therefore, MVCA can better improve the safety of intelligent vehicles. The simulation was conducted in MATLAB, including crossroads scene simulation and circular exchange position simulation. The results show that MVCA behaves safely and reliably. The effects of latency and packet loss on MVCA are also statistically investigated through theoretically formulating broadcasting process based on one-dimensional Markov chain. The results uncover that the tolerant delay should not exceed the half of deciding cycle of trajectory planning, and shortening the sending interval could alleviate the negative effects caused by the packet loss to an extent. The cases of short delay ( less than 100 ms ) and low packet loss ( less than 5% ) can bring little influence to those trajectory planning algorithms that only depend on V2V to sense the context, but the unpredictable collision may occur if the delay and packet loss are further worsened. The MVCA was also tested by a real intelligent vehicle, the test results prove the operability of MVCA.

Mobile Robot Based Online Chinese Chess Game

Abstract: We present the game tree search techniques based on Chinese chess game, and use mobile robots to present the scenario. We design a mobile robot to be applied in many fields, such as entertainment, education and security. The mobile robot has the shape of cylinder and its diameter, height and weight is 8cm, 15cm and 1.5kg. The power of the mobile robot is three Li batteries, and connects with parallel arrangement. It has three IR sensors to detect obstacle. The controller of the mobile robot is MCS-51 chip, and can acquire the detection signal from sensors through I/O pins, and receives the command from the supervised computer and the remote controller via wireless RF interface. The controller of the mobile robot can transmits the detection result to the supervised computer via wireless RF interface. The mobile robot can speak Chinese language using voice driver module. We develop the user interface of mobile robots according to the basic rules of Chinese chess game, and program the motion trajectories for the mobile robot to play the Chinese chess game. In the experimental results, mobile robots can receive the command from the supervised computer, and move the next position according to the attribute of the chess piece.

Multi-objective path planning for space exploration robot based on chaos immune particle swarm optimization algorithm

Abstract: Multi-objective path planning for mobile robot in complex environments is a challenging issue in space exploration. In order to improve the efficiency and quality of the multi-objective path planning, a chaos immune particle swarm optimization (CIPSO) algorithm is proposed in this paper, which combines chaos and PSO with immune network theory so as to enhance the searching speed of path planning for mobile robot and insure the safety of space exploration. Simulation results show that the CIPSO has well performance for path planning and obstacle avoidance.

UAV Flocks Forming for Crowded Flight Environments.

Abstract: In this study, we consider a situation where several privately owned unmanned aerial vehicles (UAVs) are supposed to travel on several routes. We develop a model for grouping them into UAV flocks that are supposed to travel on similar routes within the same time window. Our proposed flocking protocol enables each UAV to optimize its own preferences concerning its flights. Using this protocol enables all UAVs to enjoy freer routes and fewer encounters with other UAVs, thus saving time and energy during their flights. The protocol allows each UAV to create a flock or to join an existing flock to save its resources. Joining flocks in a crowded environment can reduce the overhead caused by encountering additional UAVs in the environment. We developed a flocking protocol that allows each UAV to design its optimal route. The protocol is based on a public on-line communication blackboard, which enables each UAV to receive information about existing flocks, join an existing flock or build a new flock and publish it on the blackboard. In addition, we defined a strategy for each UAV to assist in deciding which flock to join or whether to create a new flock to optimize its expected utility. Finally, the effectiveness of the proposed algorithm is verified by means of simulations.

Robot Assisted Wireless Sensor Network for Monitoring and Detection of Explosives in Indoor Environment

Abstract: In recent years, remote environment monitoring has been significantly improved with wireless sensor networking technology. This paper presents the real time streaming of an indoor environment using a wireless sensor network and a set of self-navigating robots. Mobile robots with mounted sensors will autonomously navigate through an indoor area with unknown obstacles. The robots will be able to avoid obstacles and move around the region. The robots sense the environmental parameters of the region, and send that data to the remote monitoring terminals using an underlying wireless sensor network. This design is applicable to networks where some of the sensors may not have sufficient range to sense data more accurately and closer monitoring is required. Effective path planning for the mobile robot is achieved by combining a map of the area, the sensor readings and the radio strength of the sensor network. Email alerts can be sent to officials if the sensed data goes above a predefined threshold level, thus successfully detecting the presence of explosives in a given area. This system streams the data in real- time to the Internet making it possible for authorized personnel to view the status of the environment online.