39 accepted papers
Robotic bin packing is widely deployed in warehouse automation, with current systems achieving robust performance through heuristic and learning-based strategies. These systems must balance compact placement with rapid execution, where selecting alternative items or reorienting them can improve spac…
Many manufacturing companies are facing an acute shortage of qualified workers. Deploying robotic cells is a potential solution to address this challenge. Historically robots have been deployed only in mass production applications in manufacturing. A large fraction of manufacturing is classified as…
Disassembly is a critical challenge in maintenance and service tasks, particularly in high-precision operations such as electric vehicle (EV) battery recycling. Tasks like prying-open sealed battery covers require precise manipulation and controlled force application. In our approach we collect huma
The growing adoption of batteries in the electric vehicle industry and various consumer products has created an urgent need for effective recycling solutions. These products often contain a mix of compliant and rigid components, making robotic disassembly a critical step toward achieving scalable re
Many applications require the deployment of legged-robot teams to effectively and efficiently carry out missions. The use of multiple robots allows tasks to be executed concurrently, expediting mission completion. It also enhances resilience by enabling task transfer in case of a robot failure. This…
In recent years, the field of legged robotics has seen growing interest in enhancing the capabilities of these robots through the integration of articulated robotic arms. However, achieving successful loco-manipulation, especially involving interaction with heavy objects, is far from straightforward…
Multi-robot systems are becoming increasingly prevalent in various real-world applications, such as manufacturing and warehouse logistics. These systems face complex challenges in 1) task allocation due to factors like time-extended tasks, and agent specialization, and 2) uncertainties in task execu…
Suction cups are popular for picking and transporting packages in warehouse applications. To maximize throughput, high transport speeds are desired. Many packages are deformable and may detach from the suction cups due to inertial loading if trajectories use excessive velocities. This paper introduc…
We address the challenge of transferring human preferences for action selection from simpler source tasks to complex target tasks. Our goal is to enable robots to support humans proactively by predicting their actions — without requiring demonstrations of their preferred action sequences in the targ
Bin-packing is an important problem in the robotic warehouse domain. Traditionally, this problem has been studied only for rigid packages (e.g., boxes or rigid objects). In this work, we tackle the problem of bin-packing with deformable packages that have become a popular choice for fulfillment need…
In manufacturing, minimizing operational delays is crucial for efficiency and resilience. Therefore, efficiently handling contingencies is essential in human-robot teams working on assembly (i.e., collaborative assembly) applications. This paper introduces a novel approach to generating contingency…
Recent studies on quadruped robots have focused on either locomotion or mobile manipulation using a robotic arm. However, legged robots can manipulate large objects using non-prehensile manipulation primitives, such as planar pushing, to drive the object to the desired location. This paper presents…
We consider the problem of task assignment and scheduling for human-robot teams to enable the efficient completion of complex problems, such as satellite assembly. In high-mix, low volume settings, we must enable the human-robot team to handle uncertainty due to changing task requirements, potential…
In this work, we present an inverse reinforcement learning approach for solving the problem of task sequencing for robots in complex manufacturing processes. Our proposed framework is adaptable to variations in process and can perform sequencing for entirely new parts. We prescribe an approach to ca…
Screw-driving is an important operation in numerous applications. In many situations, hole pose cannot be estimated very accurately. Autonomous screw-driving cannot be performed by traditional industrial manipulators in position control mode when the hole pose uncertainty is high. This paper present…
Testing and evaluation of field robotic systems requires both experimentation in representative conditions and human supervision to effectively assess components, manage risk, and interpret results. Due to the complexity of robotic sys-tems, we argue this experimentation should be done adaptively by…
Wire arc additive manufacturing is a metal additive manufacturing process in which the material is deposited using arc welding technology. It is gaining popularity due to high material deposition rates and faster build time. It is en-abled using robotic manipulators and can build relatively large-sc…
Composites are increasingly becoming a material of choice in the aerospace and automotive industries. Currently, many composite parts are produced by manually laying up sheets on complex molds. Composite sheet layup requires executing two main tasks: (1) grasping a sheet and (2) draping it on the mo…
Robotic manipulators are increasingly being used to perform additive manufacturing. The accuracy of a built part is dependent on the trajectory execution error of the manipulator. For articulated manipulators, the trajectory execution error and achievable build accuracy vary considerably over the wo…
To effectively assist human workers in assembly tasks a robot must proactively offer support by inferring their preferences in sequencing the task actions. Previous work has focused on learning the dominant preferences of human workers for simple tasks largely based on their intended goal. However,…
Determining a feasible path for nonholonomic mobile manipulators operating in congested environments is challenging. Sampling-based methods, especially bi-directional tree search-based approaches, are amongst the most promising candidates for quickly finding feasible paths. However, sampling uniform…
In a mission with considerable uncertainty due to intermittent communications, degraded information flow, and failures, humans need to assess both the current and expected future states, and update task assignments to robots as quickly as possible. We present a forward simulation-based alert system…
Multi-arm mobile manipulators can be represented as a combination of multiple robotic agents from the perspective of task-assignment and motion planning. Depending upon the task, agents might collaborate or work independently. Integrating motion planning with task-agent assignment is a computational…
High-performance composites are increasingly being used in the industry. Sheet layup is a process of manufacturing composite components using deformable sheets. We have developed a robotic cell to automate the layup process and overcome the limitations of the manual layup. Generating offline traject…
Extrusion-based additive manufacturing (AM), also known as fused deposition modeling (FDM) extrudes filaments through a heated nozzle and builds a part layer-by-layer. Using a smaller diameter nozzle can achieve better surface finish. However, there is a trade-off between surface finish and build ti…
Currently, automatically generated trajectories cannot be directly used on tasks that require high execution accuracies due to errors accused by inaccuracies in the robot model, actuator errors, and controller limitations. These trajectories often need manual refinement. This is not economically via…
We present a context-dependent bi-directional tree-search framework for point-to-point path planning for manipulators. Conceptually, our framework is composed of six modules: tree selection, focus selection, node selection, target selection, extend selection and connection type selection. Each modul…
We pose the problem of path-constrained trajectory generation for the synchronous motion of multi-robot systems as a non-linear optimization problem. Our method determines appropriate parametric representation for the configuration variables, generates an approximate solution as a starting point for…
Successfully completing a complex manufacturing task requires finding a feasible placement of the workpiece in the robot workspace. The workpiece placement should be such that the task surfaces on the workpiece are reachable by the robot, the robot can apply the required forces, and the end-effector…
In this paper, we investigate the use of surrogate agents to accelerate test scenario generation for autonomous vehicles. Our goal is to train the surrogate to replicate the true performance modes of the system. We create these surrogates by utilizing imitation learning with deep neural networks. By…
To properly evaluate the ability of robots to operate autonomously in the real world, it is necessary to develop methods for quantifying their self-righting capabilities. Here, we improve upon a sampling-based framework for evaluating self-righting capabilities that was previously validated in two d
We propose a scalable, parallelizable policy synthesis framework intended for a robot presented with the decision of exploration or rescue, given some time-varying, stochastic mission conditions, referred to as context. We demonstrate the feasibility of such a solution using physics-based simulation…
In this letter, an approach is presented to estimate the stiffness characteristics of elastically deformable objects, while being processed in a robotic cleaning system. Building on our previous work [J. D. Langsfeld, A. M. Kabir, K. N. Kaipa, and S. K. Gupta, “Robotic bimanual cleaning of deformabl
In this work, we present a Stochastic Gradient Ascent (SGA) algorithm for multi-vehicle information gathering that accounts for limitations on a vehicle's control authority caused by external forces. By representing vehicle paths using a novel action space representation, rather than a state space r…
Use of robots is rising in process applications where robots need to interact with parts using tools. Representative examples can be cleaning, polishing, grinding, etc. These tasks can be non-repetitive in nature and the physics-based models of the task performances are unknown for new materials and…
We propose a novel method for generating test scenarios for a black box autonomous system that demonstrate critical transitions in its performance modes. In complex environments it is possible for an autonomous system to fail at its assigned mission even if it complies with requirements for all subs…
Motion planning for multi-target autonomous search requires efficiently gathering as much information over an area as possible with an imperfect sensor. In disaster scenarios and contested environments the spatial connectivity may unexpectedly change (due to aftershock, avalanche, flood, building co…
In this paper, we consider the problem of guarding a valuable naval asset from a highly maneuverable threat via the use of autonomous unmanned surface vehicles (USVs) as dynamic obstacles. The objective of the defending agent is to maximize the amount of time it takes an intruder boat to enter the r…
Quadruped locomotion offers significant advantages over wheeled locomotion for small mobile robots operating in challenging terrain. Central pattern generators (CPGs), as found in the neural circuitry of many animals, may be used to generate joint trajectories for quadruped robots. However, basic CP…