41 accepted papers
Real-world applications of path planning must contend with complicated constraint and objective functions imposed by the surrounding operational and regulatory environment. Traditional methods such as PRM* and RRT* have asymptotic guarantees, but often struggle in practice with complex blackbox obje
We propose a decentralised multi-robot coordination algorithm that features a rich representation for encoding and communicating each robot’s intent. This representation for “intent messages” enables improved coordination behaviour and communication efficiency in difficult scenarios, such as those w…
We propose multi-horizon Monte Carlo tree search (MH-MCTS), the first framework for integrated hierarchical multi-horizon, multi-agent planning based on Monte Carlo tree search (MCTS). The method employs multiple simultaneous MCTS optimisations for each planning level within each agent, which are de
Many applications of path planning in time-varying flow fields, particularly in areas such as marine robotics and ship routing, can be modelled as instances of the time-varying shortest path (TDSP) problem. Although there are no known polynomial-time solutions to TDSP in general, our recent work has…
We consider the coordinated escort problem, where a decentralised team of supporting robots implicitly assist the mission of higher-value principal robots. The defining challenge is how to evaluate the effect of supporting robots' actions on the principal robots' mission. To capture this effect, we…
We propose an algorithm for solving the time-dependent shortest path problem in flow fields where the FIFO (first-in-first-out) assumption is violated. This problem variant is important for autonomous vehicles in the ocean, for example, that cannot arbitrarily hover in a fixed position and that are…
Improving the safety and efficiency of maritime shipping has the potential to reduce carbon emissions and improve profitability. Stochastic ship routing, the problem of finding a safe, efficient, and timely route for a ship is difficult in large part because of uncertainty in weather forecasts, whic…
Trajectory prediction in a cluttered environment is key to many important robotics tasks such as autonomous navigation. However, there are an infinite number of possible trajectories to consider. To simplify the space of trajectories under consideration, we utilise homotopy classes to partition the…
Climbing robots have the potential to revolutionize the maintenance and inspection operations of many types of vertical structures. In nature, parrots exhibit a remarkable capacity for manipulation during climbing behaviors, for which robotics can benefit from studying. In this paper we present a no…
We present a new algorithm for coordinating the motion of multiple extruders to increase throughput in fused filament fabrication (FFF)/fused deposition modeling (FDM) additive manufacturing. Platforms based on FFF are commonly available and advantageous to several industries, but are limited by slo…
We present a planning framework for min-imising the deterministic worst-case error in sparse Gaus-sian process (GP) regression. We first derive a univer-sal worst-case error bound for sparse GP regression with bounded noise using interpolation theory on reproducing kernel Hilbert spaces (RKHSs). By…
Estimating ocean flow fields in 3D is a critical step in enabling the reliable operation of underwater gliders and other small, low-powered autonomous marine vehicles. Existing methods produce depth-averaged 2D layers arranged at discrete vertical intervals, but this type of estimation can lead to s…
Heterogeneous multi-robot systems are advantageous for operations in unknown environments because functionally specialised robots can gather environmental information, while others perform tasks. We de ne this decomposition as the scout–task robot architecture and show how it avoids the need to expl…
We present a method to estimate two-dimensional, time-invariant oceanic flow fields based on data from both ensemble forecasts and online measurements. Our method produces a realistic estimate in a computationally efficient manner suitable for use in marine robotics for path planning and related app…
Systems of multiple low-cost, underactuated floats combined with fully actuated surface vessels can improve the scalability and cost-effectiveness of autonomous systems for marine science and environmental monitoring. Here, we consider a coordination problem where surface vessels must drop off float…
We present a path planning framework for marine robots subject to uncertain ocean currents that exploits data from ensemble forecasting, which is a technique for current prediction used in oceanography. Ensemble forecasts represent a distribution of predicted currents as a set of flow fields that ar…
We reformulate the signal temporal logic (STL) synthesis problem as a maximum a-posteriori (MAP) inference problem. To this end, we introduce the notion of random STL (RSTL), which extends deterministic STL with random predicates. This new probabilistic extension naturally leads to a synthesis-as-in…
Dormant pruning is a major cost component of fresh market tree fruit production, nearly equal in scale to harvesting the fruit. However, relatively little focus has been given to the problem of pruning trees autonomously. In this paper, we introduce a robotic system consisting of an industrial manip…
In this letter, we propose a low-cost, high-efficiency framework for cooperative active pose-graph simultaneous localization and mapping (SLAM) for multiple robots in three-dimensional (3D) environments based on graph topology. Based on the selection of weak connections in pose graphs, this method a
Motion planning for vehicles under the influence of flow fields can benefit from the idea of streamline-based planning, which exploits ideas from fluid dynamics to achieve computational efficiency. Important to such planners is an efficient means of computing the travel distance and direction betwee…
Gaussian processes (GPs) enable a probabilistic approach to important estimation and classification tasks that arise in robotics applications. Meanwhile, most GP-based methods are often prohibitively slow, thereby posing a substantial barrier to practical applications. Existing "sparse" methods to s…
We present an efficient approach for finding shortest paths in flow fields that vary as a sequence of flow predictions over time. This approach is applicable to motion planning for slow marine robots that are subject to dynamic ocean currents. Although the problem is NP-hard in general form, we inco…
Multi-modal estimation systems have the advantage of increased accuracy and robustness. To achieve accurate sensor fusion with these types of systems, a reliable extrinsic calibration between each sensor pair is critical. This paper presents a novel self-calibration framework for lidar-inertial syst…
The most widely used methods for toolpath planning in 3D printing slice the input model into successive 2D layers to construct the toolpath. Unfortunately the methods can incur a substantial amount of wasted motion (i.e., the extruder is moving while not printing). In recent years we have introduced…
We consider the problem of reconstructing regions of interest of a scene using multiple robot arms and RGB-D sensors. This problem is motivated by a variety of applications, such as precision agriculture and infrastructure inspection. A viewpoint evaluation function is presented that exploits predic…
In this paper, we present an on-line active pose-graph simultaneous localization and mapping (SLAM) frame-work for robots in three-dimensional (3D) environments using graph topology and sub-maps. This framework aims to find the best trajectory for loop-closure by re-visiting old poses based on the T…
Underwater robots are subject to position drift due to the effect of ocean currents and the lack of accurate localisation while submerged. We are interested in exploiting such position drift to estimate the ocean current in the surrounding area, thereby assisting navigation and planning. We present…
Autonomous underwater gliders frequently execute extensive missions with high levels of uncertainty due to limitations of sensing, control and oceanic forecasting. Glider path planning seeks an optimal path with respect to conflicting objectives, such as travel cost and safety, that must be explicit…
Motion planning for underwater vehicles must consider the effect of ocean currents. We present an efficient method to compute reachability and cost between sample points in sampling-based motion planning that supports long-range planning over hundreds of kilometres in complicated flows. The idea is…
We consider a multi-robot variant of the mission monitoring problem. This problem arises in tasks where a robot observes the progress of another robot that is stochastically following a known trajectory, among other applications. We formulate and solve a variant where multiple tracker robots must mo…
The active SLAM problem considered in this paper aims to plan a robot trajectory for simultaneous localization and mapping (SLAM) as well as for an area coverage task with robot pose uncertainty. Based on a model predictive control (MPC) framework, these two problems are solved respectively by diffe…
We present an algorithm for selecting when to communicate during online planning phases of coordinated multi-robot missions. The key idea is that a robot decides to request communication from another robot by reasoning over the predicted information value of communication messages over a sliding tim…
Autonomous Science is a field of study which aims to extend the autonomy of exploration robots from low level functionality, such as on-board perception and obstacle avoidance, to science autonomy, which allows scientists to specify missions at task level. This will enable more remote and extreme en…
This paper presents an extension of Gaussian process implicit surfaces (GPIS) by the introduction of geometric object priors. The proposed method enhances the probabilistic reconstruction of objects from three-dimensional (3-D) pointcloud data, providing a rigorous way of incorporating prior knowled
Multi-robot information gathering teams typically require communication for data fusion and cooperative decision making. However, when communication takes place over wireless networks, stringent bandwidth limits apply. These limits raise the need for efficient utilisation of available communication…
The informative soaring (IFS) problem involves a gliding unmanned aerial vehicle (UAV) exploiting energy from thermals to extend its information gathering capability. In this paper, we address the realistic situation of detecting new thermals drifting with the wind in the search environment. We cons
We propose a self-organising map (SOM) algorithm as a solution to a new multi-goal path planning problem for active perception and data collection tasks. We optimise paths for a multi-robot team that aims to maximally observe a set of nodes in the environment. The selected nodes are observed by visi…
We present an end-to-end method for active object classification in cluttered scenes from RGB-D data. Our algorithms predict the quality of future viewpoints in the form of entropy using both class and pose. Occlusions are explicitly modeled in predicting the visible regions of objects, which modula
We consider an optimal stopping formulation of the mission monitoring problem, where a monitor vehicle must remain in close proximity to an autonomous robot that stochastically follows a pre-planned trajectory. This problem arises when autonomous underwater vehicles are monitored by surface vessels,…
Contextual cues can provide a rich source of information for robots that operate in the presence of other agents such as people, animals, vehicles and fellow robots. We are interested in context, in the form of the behavioural intent of an agent, for enhanced trajectory prediction. We present a Baye…
The application of autonomous robots to efficiently locate small wildlife species has the potential to provide significant ecological insights not previously possible using traditional land-based survey techniques, and a basis for improved conservation policy and management. We present an approach f…