Related papers: Path Planning of Unmanned System using Carrot-chas…
In this article, we address the control problem of unicycle path following, using a rigidly attached target point. The initial path following problem has been transformed into a reference trajectory following problem, using saturated…
In this paper, an original heuristic algorithm of empty vehicles management in personal rapid transit network is presented. The algorithm is used for the delivery of empty vehicles for waiting passengers, for balancing the distribution of…
This article establishes the Exploration-RRT algorithm: A novel general-purpose combined exploration and pathplanning algorithm, based on a multi-goal Rapidly-Exploring Random Trees (RRT) framework. Exploration-RRT (ERRT) has been…
In this paper, a novel knowledge-based genetic algorithm for path planning of a mobile robot in unstructured complex environments is proposed, where five problem-specific operators are developed for efficient robot path planning. The…
Swarms of collaborating Unmanned Aerial Vehicles (UAVs) that utilize ad-hoc networking technologies for coordinating their actions offer the potential to catalyze emerging research fields such as autonomous exploration of disaster areas,…
This paper presents a method for path-following for quadcopter trajectories in real time. Non-Linear Guidance Logic is used to find the intercepts of the subsequent destination. Trajectory tracking is implemented by formulating the…
In this article, a novel time-coordination algorithm based on event-triggered communications is proposed to achieve coordinated path-following of UAVs. To be specific, in the approach adopted a UAV transmits its progression information over…
This paper proposes a control algorithm for a UAV to circumnavigate an unknown target at a fixed radius when the location information of the UAV is unavailable. By assuming that the UAV has a constant velocity, the control algorithm makes…
Drones are being used in many industries for a variety of applications, including inspecting bridges, surveying farm land, and delivering cargo. Automating these kinds of scenarios requires more than following a sequence of GPS waypoints;…
This paper presents a new connectivity condition on the information flow between UAVs to achieve coordinated path following. The information flow is directional, so that the underlying communication network topology is represented by a…
Mobile robots often have limited battery life and need to recharge periodically. This paper presents an RRT- based path-planning algorithm that addresses battery power management. A path is generated continuously from the robot's current…
Motion trajectory planning is one crucial aspect for automated vehicles, as it governs the own future behavior in a dynamically changing environment. A good utilization of a vehicle's characteristics requires the consideration of the…
This study presents a new methodology for learning-based motion planning for autonomous exploration using aerial robots. Through the reinforcement learning method of learning through trial and error, the action policy is derived that can…
Search-based motion planning algorithms have been widely utilized for unmanned aerial vehicles (UAVs). However, deploying these algorithms on real UAVs faces challenges due to limited onboard computational resources. The algorithms struggle…
In this paper, a robot navigating an environment shared with humans is considered, and a cost function that can be exploited in $\text{RRT}^\text{X}$, a randomized sampling-based replanning algorithm that guarantees asymptotic optimality,…
We present an algorithm for steering the output of a linear system from a feasible initial condition to a desired target position, while satisfying input constraints and non-convex output constraints. The system input is generated by a…
In robotics, coordinating a group of robots is an essential task. This work presents the communication-constrained multi-agent multi-goal path planning problem and proposes a graph-search based algorithm to address this task. Given a fleet…
Modern autonomous driving algorithms often rely on learning the mapping from visual inputs to steering actions from human driving data in a variety of scenarios and visual scenes. The required data collection is not only labor intensive,…
Mobile robots rely on maps to navigate through an environment. In the absence of any map, the robots must build the map online from partial observations as they move in the environment. Traditional methods build a map using only direct…
Automated driving in urban scenarios requires efficient planning algorithms able to handle complex situations in real-time. A popular approach is to use graph-based planning methods in order to obtain a rough trajectory which is…