32 accepted papers
Though robotic systems are now being commercialized and deployed in various industries, many of these systems are highly specialized and often require an advanced skill set to operate and ensure they perform as instructed. To mitigate this problem, it has been proposed to use large language models (…
This paper explores decision-making processes in robotic systems tasked with reconstructing scalar fields through sensing in uncertain environments. Each robot must handle noisy perception and operate within specific environmental and physical constraints. The complexity increases in multiagent scen
Robotics and artificial intelligence hold significant potential for advancing precision agriculture. While robotic systems have been successfully deployed for various tasks, adapting them to perform diverse missions remains challenging, particularly because end users often lack technical expertise.
For robots tasked with surveying the temporal dynamics of a changing environment, a choice must be made to observe novel regions of the environment or to re-survey previously visited regions, which may have changed. We present a novel multi-robot informative path planner (IPP) that combines an envir
Graph patrolling algorithms provide effective strategies for coordinating mobile robots in the context of autonomously surveilling valuable assets. Optimizing patrolling strategies often aims to minimize the time between subsequent visits to a vertex, a measure known in the literature as idleness. I…
In multi-robot informative path planning the problem is to find a route for each robot in a team to visit a set of locations that can provide the most useful data to reconstruct an unknown scalar field. In the budgeted version, each robot is subject to a travel budget limiting the distance it can tr…
The ROS 2 Navigation Stack (Nav2) has emerged as a widely used software component providing the underlying basis to develop a variety of high-level functionalities. However, when used in outdoor environments such as orchards and vineyards, its functionality is notably limited by the presence of obst…
Graph-patrolling problems in the adversarial domain typically embed models and assumptions about how hostile events, from which an environment must be protected, are generated at a specific time and location. Relying upon such attacker models prevents algorithms from synthesizing strategies that can…
The proliferation of unmanned vehicles offers many opportunities for solving environmental sampling tasks with applications in resource monitoring and precision agriculture. Informative path planning (IPP) includes a family of methods which offer improvements over traditional surveying techniques fo…
We present a novel algorithm to solve the stochastic orienteering problem with chance constraints that combines Monte Carlo Tree Search (MCTS) with a best arm identification (BAI) algorithm. This method extends our recently proposed solution that builds a search planning tree considering both an obj…
In this paper we consider the information path-planning problem for a single robot in a stochastic environment with static obstacles subject to a preassigned constraint on the distance it can travel. Given a set of candidate sampling locations, the objective is to determine a path for the robot that…
We consider the Stochastic Orienteering Problem with random traversal time for edges. In this scenario the length of the path is a random variable and we consider a formulation with chance constraints, i.e., a bound on the probability that the length of the path exceeds the allotted budget. Our prop…
We study a stochastic version of the classic orienteering problem where the time to traverse an edge is a continuous random variable. For a given temporal deadline B, our solution produces a policy, i.e., a function that, based on the current position along a solution path and the elapsed time, deci…
We consider the NP-hard Stochastic Orienteering Problem, where the goal is to navigate between start and end vertices in a graph, maximizing the sum of rewards for visited vertices while obeying a travel budget over edges with stochastic cost within a given probability of failure. Previously, we sol
Polyculture farming is a sustainable farming technique based on synergistic interactions between differing plant types that make them more resistant to diseases and pests and better able to retain water. Reduced uniformity can reduce use of pesticides, fertilizer, and water, but is more labor intens…
This work addresses task planning under uncertainty for precision agriculture applications whereby task costs are uncertain and the gain of completing a task is proportional to resource consumption (such as water consumption in precision irrigation). The goal is to complete all tasks while prioritiz
We study a patrolling problem where multiple agents are tasked with protecting an environment where one or more adversaries are trying to compromise targets of varying value. The objective of the patrollers is to move between targets to quickly spot when an attack is taking place and then diffuse it…
In this paper, we consider the Constant-cost Orienteering Problem (COP) where a robot, constrained by a limited travel budget, aims at selecting a path with the largest reward in an aisle-graph. The aisle-graph consists of a set of loosely connected rows where the robot can change lane only at eithe…
In this paper we consider the stochastic cost orienteering problem, i.e., a version of the classic orienteering problem where the cost associated with each edge is a random variable with known distribution. Such a model is relevant when travel costs are variable, e.g., when a robot moves in uncertai…
The use of autonomous robots for surveillance is one of the most interesting applications of graph-patrolling algorithms. In recent years, considerable effort has been devoted to tackling the problem of efficiently computing effective patrolling strategies. One of the mainstream approaches is advers…
In this paper we propose a new approach to evaluate grasps that accounts for both the kinematic structure of the robot and the noise at its joints. Our starting observation is that with a redundant robot the same grasp can be implemented with different arm configurations, and these may display signi…
In this paper, we consider the problem of maintaining and restoring connectivity among a set of agents (humans or robots) by incrementally redeploying a team of mobile robots acting as communication relays. This problem is relevant in numerous scenarios where humans and robots are jointly deployed f…
Indoor plants in homes and commercial buildings such as malls, offices, airports, and hotels, can benefit from precision irrigation to maintain healthy growth and reduce water consumption. As active valves are too costly, and ongoing precise manual adjustment of drip emitters is impractical, we expl…
When robots navigate through vineyards to perform irrigation adjustments, an optimization problem emerges whereby robots are tasked with performing adjustments having the highest cumulative outcome within a given temporal budget due to limited battery charge. To this end, the robot needs to reach a…
We consider the problem of grasping concave objects, i.e., objects whose surface includes regions with negative curvature. When a multifingered hand is used to restrain these objects, these areas can be advantageously used to determine grasps capable of more robustly resisting to external disturbanc…
We consider the problem where a team of mobile robots is tasked with collecting information about a set of stationary targets. There is a temporal deadline to complete the task, and the objective is to determine a control policy maximizing the probability of successfully completing the task within t
We present an algorithm to solve a sequential stochastic decision making problem whereby a robot is subject to multiple objective functions and is asked to complete a number of subgoals specified using a subset of linear temporal logic. Each subgoal is associated with a desired satisfaction probabil
In this paper we present an algorithm to compute risk averse policies in Markov Decision Processes (MDP) when the total cost criterion is used together with the average value at risk (AVaR) metric. Risk averse policies are needed when large deviations from the expected behavior may have detrimental…
We consider the problem of providing surveillance to a grid area using multiple heterogeneous UAVs, named sentinels and searchers, with complementary sensing and actuation capabilities. We consider probabilistic attacks and we analyze the expected performance with respect to the team deployment. We…
We present Partial Quick Hull (PQH), an algorithm to efficiently compute one of the most commonly used grasp quality metrics. The metric relies on the computation of the convex hull of a set of points in a six dimensional space. Built on top of widely used QuickHull algorithm, PQH exploits the relat…
In this paper we present an algorithm to determine the location of contact points to obtain force closure grasps on tree dimensional objects. The shape of the object is assumed to be given by a triangle mesh - a format widely used in CAD software. Our algorithm can handle an arbitrary number of cont…
Constrained Markov Decision Processes offer a principled way to tackle sequential decision problems with multiple objectives. Although they could be very valuable in numerous robotic applications, to date their use has been quite limited. One of the reasons is that their solution requires to solve c…