Mobile robot, especially wheeled mobile robot, with its simple mechanical structure and inherent agility, has attracted significant attentions for dynamic environment applications in the last two decades (Pin et al. 1994 and Purwin 2006). A general mobile robot Guidance, Navigation and Control (GNC) system is illustrated in the following figure. The main function of guidance system is to genera...

We present PRM-RL, a hierarchical method for long-range navigation task completion that combines samplingbased path planning with reinforcement learning (RL) agents. The RL agents learn short-range, point-to-point navigation policies that capture robot dynamics and task constraints without knowledge of the large-scale topology, while the sampling-based planners provide an approximate map of the...

This work presents the development and implementation of a biologically inspired navigation system on the autonomous Psikharpax rodent robot. Our system comprises two independent navigation strategies: a taxon expert and a planning expert. The presented navigation system allows the robot to learn the optimal strategy in each situation, by relying upon a strategy selection mechanism. Keywords— R...

We create a mapping system and a control system on a telepresence robot to further facilitate indoor social navigation. The implementation is based on a commercial telepresence robot and its custom operating system. A mapping framework based on SLAMmethods is employed to obtain real-time results. Navigation controls are implemented with inspection of the internal interfaces of the telepresence ...

An experimental approach on the online sensor based navigation of a mobile robot in unknown environment is presented. Based on the range data from the equipped range scanner on the robot, the mobile robot rather finding passable free space to approach the given goal. Experimental setups, simple navigation algorithm implemented and experimental results are presented.

Navigation and application functionality of mobile robots rely on their collision-avoiding capabilities, also known as local navigation. We present the mobile robot ARTOS (Autonomous Robot for Transport and Service) that is particularly designed to operate in living environments and therefore faces the problem of fuzzy and unstructured obstacles. The local navigation architecture is motivated r...

Deep reinforcement learning (DRL) demonstrates its potential in learning a model-free navigation policy for robot visual navigation. However, the data-demanding algorithm relies on a large number of navigation trajectories in training. Existing datasets supporting training such robot navigation algorithms consist of either 3D synthetic scenes or reconstructed scenes. Synthetic data suffers from...

This contribution presents Soft Computing Robot Navigation for mobile robot SCORCAS, a Case Study. The Navigation uses fuzzy logic experienced on mobile robot systems. Fuzzy logic is applied in analogous way into three sub-systems: i. Sensor, consisting of five autonomous sensor sub-systems: visual, acoustic, tactile, thermal and inertial; ii. Sensor fusion that comprise all the robot stimulus ...

One of the standing challenging aspects in mobile robotics is the ability to navigate autonomously. It is a difficult task, which requiring a complete modeling of the environment. This paper presents an intelligent navigation method for an autonomous mobile robot which requires only a scalar signal like a feedback indicating the quality of the applied action. Instead of programming a robot, we ...

We present a method for wheeled mobile robot navigation based on the proportional navigation law. This method integrates the robot’s kinematics equations and geometric rules. According to the control strategy, the robot’s angular velocity is proportional to the rate of turn of the angle of the line of sight that joins the robot and the goal. We derive a relative kinematics system which models t...