17 accepted papers
In agriculture, understanding the distribution and relationship between different aspects of the environment is important for minimizing chemical use and reducing environmental impact. Traditionally, it is done by manually collecting samples on the field and then sending them to a laboratory for ana
The efficient collection of samples is an important factor in outdoor information gathering applications on account of high sampling costs such as time, energy, and potential destruction to the environment. Utilization of available a-priori data can be a powerful tool for increasing efficiency. Howe…
Trajectory optimization of sensing robots to actively gather information of targets has received much attention in the past. It is well-known that under the assumption of linear Gaussian target dynamics and sensor models the stochastic Active Information Acquisition problem is equivalent to a determ…
State of the art methods for robotic path planning in dynamic environments, such as crowds or traffic, rely on hand crafted motion models for agents. These models often do not reflect interactions of agents in real world scenarios. To overcome this limitation, this paper proposes an integrated path…
Understanding and predicting the intention of pedestrians is essential to enable autonomous vehicles and mobile robots to navigate crowds. This problem becomes increasingly complex when we consider the uncertainty and multimodality of pedestrian motion, as well as the implicit interactions between m
Soft strain resistive sensors based on eutectic gallium-indium liquid metal can play an important role in proprioceptive sensing for soft robots. However, there are no available mathematical models to accurately estimate the strain as a function of the measured resistance. Furthermore, non-uniform s…
The control of field robots in varying and uncertain terrain conditions presents a challenge for autonomous navigation. Online estimation of the wheel-terrain slip characteristics is essential for generating the accurate control predictions necessary for tracking trajectories in off-road environment…
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
Actively articulated wheel-on-leg rovers offer high degrees of mobility for traversing unstructured and scientifically interesting terrain. An ability to actively conform to the terrain to increase traversability is sought. A kinematic model based on recursive kinematic propagation in combination wi
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 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
Autonomous docking for airborne energy transfer is an important unmanned aerial vehicle capability that has yet to be accomplished. The implications of this technology are far reaching because vehicle endurance can be significantly extended without requiring additional onboard energy storage or envi…
Unmanned aerial vehicle (UAV) capability is currently limited by the amount of energy that can be stored onboard. Airborne docking, for mid-air refueling, is a viable solution that has been implemented with manned aircraft for decades, but has yet to be achieved with their unmanned counterparts. The…
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…