The paper deals with the generation of optimal trajectories for industrial robots in machining and additive manufacturing applications. The proposed method uses an Ant Colony algorithm to solve a kinodynamic motion planning problem. It exploits the k...
The achievement of full autonomy in Unmanned Aerial Vehicles (UAVs) is significantly dependent on effective motion planning. Specifically, it is crucial to plan collision-free trajectories for smooth transitions from initial to final configurations....
Fixed-wing UAVs have shown great potential in both military and civilian applications. However, achieving safe and collision-free flight in complex obstacle environments is still a challenging problem. This paper proposed a hierarchical two-layer fix...
Motion planning is a fundamental problem in robotics that involves determining feasible or optimal paths within finite time. While complete motion planning algorithms are guaranteed to converge to a path solution in finite time, they are proven to be...
Motion planning and control for articulated logistic vehicles such as tugger trains is a challenging problem in service robotics. The case of tugger trains presents particular difficulties due to the kinematic complexity of these multiarticulated veh...
Finding the time-optimal parameterization of a given path subject to kinodynamic constraints is a critical topic in many robotic applications. However, designing a real-time motion planning algorithm for specified trajectories subject to physical con...
Unmanned aerial vehicles (UAVs) are utilized for wireless communication support of Internet of Intelligent Vehicles (IoVs). Intelligent vehicles (IVs) need vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) wireless communication for real-time...
Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy...
With the rapid development of robot perception and planning technology, robots are gradually getting rid of fixed fences and working closely with humans in shared workspaces. The safety of human-robot coexistence has become critical. Traditional moti...
This work provides a generalization of the three-dimensional velocity obstacle (VO) collision avoidance strategy for nonlinear second-order underactuated systems in three-dimensional dynamic uncertain environments. A hierarchical architecture is expl...
Planning trajectories for unmanned aerial vehicles (UAVs) actively tracking a moving target poses a significant challenge. This paper introduces a motion planning system utilizing UAVs to track a dynamic target actively. The system can handle complex...
We propose a novel sampling-based approach to waypoint-constrained kinodynamic planning for a custom apple-picking machine consisting of a tractor towing two trailers, operating autonomously in an orchard. The platform must follow sparse 2D waypoints...
Autonomous high-altitude balloons are promising tools for studying dynamic environments. Their ability to navigate strong wind currents with minimal actuation makes them efficient options for scientific research. In fact, the flow in which these vehi...
Trading off the allocation of limited computational resources between front-end path generation and back-end trajectory optimization plays a key role in improving the efficiency of unmanned aerial vehicle (UAV) motion planning. In this paper, a sampl...
In practical missions, quadrotor drones frequently face the challenge of navigating through multiple predetermined waypoints in cluttered environments where the sequence of the waypoints is not specified. This study presents a comprehensive multi-way...
Addressing high dynamics, stringent non-holonomic constraints, and limited onboard computation in cooperative online trajectory planning for multiple fixed-wing UAVs in complex 3D obstacle environments, this paper proposes a Cooperative-3D-Quick-Dubi...
Quadrotor motion planning in cluttered environments presents significant challenges in achieving both computational efficiency and trajectory smoothness, particularly in low-altitude economy and intelligent energy system applications where autonomous...
Autonomous navigation on unknown uneven terrain remains a critical challenge for unmanned ground vehicle (UGV) deployed in unstructured environments such as disaster relief, wilderness exploration, and off-road logistics. Existing motion planning met...