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This paper proposes the use of path planning algorithms for AUVs in applications where the robot needs to adapt online its trajectory for inspection or safety purposes. These algorithms generate trajectories under motion constraints, which can be followed without deviations, to ensure the safety even when passing close to obstacles. View planning algorithms are also combined to decide the movements...
The paper describes the control system development of a novel hybrid autonomous vehicle - Aqua-Quad, a Multi-Rotor Vertical Take Off and Landing aircraft with environmentally hardened electronics, exchangeable sensor suite, communication links, and a solar recharge system. The key objective of this multi-modal autonomous system is to enable energy-aware ultra-long endurance autonomy to facilitate...
This paper employs a computational optimal control framework to develop a mission planning tool for a team of heterogeneous unmanned vehicles conducting a nominal mine countermeasures (MCM) mission. We first describe our motivation for developing vehicle-specific sensor models for unmanned surface and underwater vehicles working collaboratively to detect mines. Next, we describe the sonar detection...
Chance-constrained control is a difficult problem even if the considered system dynamics are linear. The difficulty stems from the facts that the chance constraints are difficult to evaluate and that the control law is nonlinear due to the constraints. In this paper, we present a novel approach to chance-constrained control, where we solve the unconstrained control problem first and then use a progressive...
Several approaches can be identified in the literature for area decomposition: Grid based methods, Cellular decomposition and Boustrophedon (or Morse) decomposition. This paper proposes a novel discretization method for the area based on computational geometry approaches. By using a Constrained Delaunay Triangulation, a complex area is segmented in cells which have the size of the projected field...
Technologies for oceans engineering are being based in autonomous solutions (mainly adaptation capabilities) able to tackle more complex maritime missions. This paper presents how an Intelligent Vehicle Control Architecture (IVCA) for marine robots deals with fault-tolerant capabilities in order to build a robust approach. The IVCA moves away from fixed mission plans and very basic diagnostics schemes...
Path planning and autonomous navigation are some of the most important challenges in mobile robotics. These are difficult tasks because the robot has to accurately and safely perform autonomous maneuverings. This paper presents a methodology to efficiently plan the trajectory of a robot in dynamic and complex environments, which it should traverse autonomously. A planner based in the AD* algorithm...
We address the problem of verifying motion plans for aerial robots in uncertain and partially-known environments. Thereby, the initial state of the robot is uncertain due to errors from the state estimation and the motion is uncertain due to wind disturbances and control errors caused by sensor noise. Since the environment is perceived at runtime, the verification of partial motion plans must be performed...
Path planning among obstacles for nonholonomic systems is a widely researched area nowadays, but it is still one of the most challenging problems in autonomous navigation. We have recently presented a rapidly exploring random tree based global planner (RTR) and a steering method (C*CS) for car-like vehicles, which uses circular and straight movements. With the aid of these two methods it is possible...
This paper presents an intention-aware online planning approach for autonomous driving amid many pedestrians. To drive near pedestrians safely, efficiently, and smoothly, autonomous vehicles must estimate unknown pedestrian intentions and hedge against the uncertainty in intention estimates in order to choose actions that are effective and robust. A key feature of our approach is to use the partially...
This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore...
Unmanned vehicles are emerging as an attractive tool for persistent monitoring tasks of a given area, but need automated planning capabilities for effective unattended deployment. Such an automated planner needs to generate collision-free coverage paths by steering waypoints to locations that both minimize the path length and maximize the amount of information gathered along the path. The approach...
We examine the problem of planning the trajectory of a robotic vehicle to gather data from a deployment of stationary sensors monitoring a set of dynamic source signals. The robotic vehicle and the sensors are equipped with wireless modems (e.g., radio in terrestrial environments or acoustic in underwater environments), which provide noisy communication across limited distances. In such scenarios,...
In this paper, we consider motion planning with long-range sensing information provided by cooperative perception. Firstly, we develop a general framework to reflect sensing uncertainty and transmission delay into motion planning. The Bayesian filter is utilized for perception belief fusion, which is then formulated into a cost function for optimal planning. With the cost map, we leverage the optimal...
This paper describes an approach to motion generation for quadrotor micro-UAV's navigating cluttered and partially known environments. We pursue a graph search method that, despite the high dimensionality of the problem, the complex dynamics of the system and the continuously changing environment model is capable of generating dynamically feasible motions in real-time. This is enabled by leveraging...
This paper presents a mission control approach and an on-board fault recovery to enable an autonomous underwater vehicle (AUV) to carry out the oceanographic survey autonomously. The challenges of AUV's operability in clutter environment have led the researchers to develop intelligent control architectures composed of distributed, independent and asynchronous behaviors, so the multi-agent system is...
This paper describes a nonholonomic robotic wheeled vehicle ripple tentacle motion planning method, aiming to improve the vehicle's trajectory smoothness and avoid frequent weight parameters adjustment in different environments. In the regular tentacle motion planning algorithm, the planning result is selected among the drivable tentacles using a weighted sum cost function. Though the method is simple...
Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles...
This paper presents a strategy for a rover navigation in initially unknown or poorly known environments. The strategy consists in determining the areas in which information is relevant to gather for the rover to reach the goal. The approach relies on a probabilistic reasoning on the currently available information on the environment, and on the models of the vehicle perception and motion abilities...
We present a hybrid path planner that combines two common methods for robotic planning: a Dijkstra graph search for the minimum distance path through the configuration space and an optimization scheme to iteratively improve grid-based paths. Our formulation is novel because we first commit to the minimum distance path, then explicitly relax the path to maximize the clearance up to a user-specified...
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