36 accepted papers
Classical graph of convex sets (GCS) formulations rely on pairwise edge costs, which are insufficient to capture higher-order geometric interactions relevant to trajectory refinement. This paper proposes a hyper graph of convex sets (HGCS), which extends GCS by introducing hyperedges over multiple v…
Multi-robot systems are increasingly deployed in high-risk missions such as reconnaissance, disaster response, and subterranean operations. Protecting a human operator while navigating unknown and adversarial environments remains a critical challenge, especially when the communication among the oper…
Multi-robot systems often need to navigate through obstacle-cluttered environments while performing complex tasks. To ensure collision-free trajectories among the robots and with the obstacles is essential for the overall safety, along with additional requirements such as dynamic feasibility, relati…
Multi-robot systems can greatly enhance efficiency through coordination and collaboration, yet in practice, full-time communication is rarely available and interactions are constrained to close-range exchanges. Existing methods either maintain all-time connectivity, rely on fixed schedules, or adopt
Multi-robot systems can greatly enhance efficiency through coordination and collaboration, yet in practice, full-time communication is rarely available and interactions are constrained to close-range exchanges. Existing methods either maintain all-time connectivity, rely on fixed schedules, or adopt…
Safe navigation within a workspace is a fundamental skill for autonomous robots to accomplish more complex tasks. Harmonic potentials are artificial potential fields that are analytical, globally convergent and provably free of local minima. Thus, it has been widely used for generating safe and reli…
Many robots are not equipped with a manipulator and many objects are not suitable for prehensile manipulation (such as boxes and large cylinders). In these cases, pushing is a simple yet effective non-prehensile skill for robots to interact with and further change the environment. Existing work ofte…
Multi-robot systems can be extremely efficient for accomplishing team-wise tasks by acting concurrently and collaboratively. However, most existing methods either assume static task features or simply replan when environmental changes occur. This paper addresses the challenging problem of coordinati…
Online coordination of multi-robot systems in open and unknown environments faces significant challenges, particularly when semantic features detected during operation dynamically trigger new tasks. Recent large language model (LLMs)-based approaches for scene reasoning and planning primarily focus
Acoustic feedback cancellation is an important task in audio processing systems, aiming to mitigate the effects of feedback loops on system stability and sound quality. State-of-the-art methods rely on adaptive filtering algorithms and face challenges in balancing between rapid convergence and low s…
Fleets of autonomous robots have been deployed for exploration of unknown scenes for features of interest, e.g., subterranean exploration, reconnaissance, search and rescue missions. During exploration, the robots may encounter un-identified targets, blocked passages, interactive objects, temporary
Multi-agent systems can be extremely efficient when working concurrently and collaboratively, e.g., for delivery, surveillance, search and rescue. Coordination of such teams often involves two aspects: (i) selecting appropriate subteams for different tasks in various areas; (ii) coordinating agents
Multi-agent trajectory planning requires ensuring both safety and efficiency, yet deadlocks remain a significant challenge, especially in obstacle-dense environments. To address this, we propose a novel distributed trajectory planning framework that bridges the gap between global path and local traj
Long-term monitoring of numerous dynamic targets can be tedious for a human operator and infeasible for a single robot, e.g., to monitor wild flocks, detect intruders, search and rescue. Fleets of autonomous robots can be effective by acting collaboratively and concurrently. However, the online coor
A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A common solution is to deploy intermediate UAVs to relay information via a multi-hop network, which introduces two challeng
Coalition is an important mean of multi-robot systems to collaborate on common tasks. An adaptive coalition strategy is essential for the online performance in dynamic and unknown environments. In this work, the problem of territory defense by large-scale heterogeneous robotic teams is considered. T
Pushing is a simple yet effective skill for robots to interact with and further change the environment. Related work has been mostly focused on utilizing it as a non-prehensile manipulation primitive for a robotic manipulator. However, it can also be beneficial for low-cost mobile robots that are no…
Fleets of unmanned robots can be beneficial for the long-term monitoring of large areas, e.g., to monitor wild flocks, detect intruders, search and rescue. Monitoring numerous dynamic targets in a collaborative and efficient way is a challenging problem that requires online coordination and informat…
Exploration of unknown scenes before human entry is essential for safety and efficiency in numerous scenarios, e.g., subterranean exploration, reconnaissance, search and rescue missions. Fleets of autonomous robots are particularly suitable for this task, via concurrent exploration, multi-sensory pe…
This letter presents a multi-robot trajectory planning method which not only guarantees optimization feasibility and but also resolves deadlocks in obstacle-dense environments. The method is proposed via formulating a recursive optimization problem, where a novel safe corridor is generated online to
Learning from demonstration (LfD) provides a fast, intuitive and efficient framework to program robot skills, which has gained growing interest both in research and industrial applications. Most complex manipulation tasks are long-term and involve a set of skill primitives. Thus it is crucial to hav…
Adaptive filters have been widely used for feedback cancellation in audio systems including hearing aids. In addition to adaptive filters, the frequency shifting has often been used to obtain an unbiased estimation of the adaptive filters, by decorrelating the incoming and outgoing signals of the au…
Learning from Demonstration (LfD) provides an intuitive and fast approach to program robotic manipulators. Task parameterized representations allow easy adaptation to new scenes and online observations. However, this approach has been limited to pose-only demonstrations and thus only skills with spa…
Acoustic feedback is one of the major problems in hearing aid applications. During a fitting session of a modern hearing aid, typically a feedback path prediction or an in situ measurement of feedback path is used as part of the gain and earpiece prescription to minimize the risk of feedback problem…
Enabling robots to quickly learn manipulation skills is an important, yet challenging problem. Such manipulation skills should be flexible, e.g., be able adapt to the current workspace configuration. Furthermore, to accomplish complex manipulation tasks, robots should be able to sequence several ski…
While the majority of binaural beamformers aim to minimize the output noise power while (approximately) preserving the binaural cues of the sources using constraints, we propose in this paper to minimize the binaural-cue distortions of the sources in the acoustic scene, such that the output noise po…
The short-time Fourier transform (STFT) and the inverse short-time Fourier transform are often used in signal analysis, modification, and synthesis. In this work, we focus on the effect of overlapping STFT subbands in relation to signal modification and synthesis. We illustrate that the subband over…
While manipulation skills such as picking, inserting and placing were hard coded in classical setups, it is now widely understood that this leads to poor flexibility and that more general skill formulations are required to ensure re-usability in new scenarios. We thus adopt a skill-centric approach
Coordinating multiple agents, such as mobile robots, with shared resources, such as common battery charging stations, is a highly relevant but still challenging decision problem. Traditionally, the motion and task planning of multi-agent systems are tackled by either designing ad-hoc decision rules
Adaptive filters have been widely used for feedback cancellation in audio systems including hearing aids. However, the ability to cancel feedback in dynamic feedback situations is still a big challenge; the adaptive filters need to ensure a small enough steady-state error to facilitate sufficient am…
This paper considers the motion control and task planning problem of mobile robots under complex high-level tasks and human initiatives. The assigned task is specified as Linear Temporal Logic (LTL) formulas that consist of hard and soft constraints. The human initiative influences the robot autonom…
We consider a team of multiple dynamical and heterogeneous robots which are deployed for gathering different types of data within a common workspace. The robots have different roles due to different capabilities: some gather data from the workspace (Type-A robots) and others receive data from Type-A…
We propose a distributed and cooperative motion and task control scheme for a team of mobile robots that are subject to dynamic constraints including inter-robot collision avoidance and connectivity maintenance of the communication network. Moreover, each agent has a local high-level task given as a
Audio applications often suffer from the acoustic feedback problem which leads to significant sound quality degradation and howling in the worst case. Many solutions exist to minimize the effect of feedback. However, it is not trivial to evaluate these solutions. In this work, we focus on intrusive…
Frequency shifting has been used for acoustic feedback control in audio reinforcement systems since the 1950s. It can be used as a stand-alone system and/or it can be combined with an acoustic feedback cancellation system using adaptive filters. A spectral shifting of the loudspeaker signal in an au…
This work focuses on an adaptive beamformer in a hearing aid application using a generalized sidelobe canceller structure (GSC). In this application, the constraint and blocking matrices in the GSC structure are specifically designed using an estimate of the transfer functions between the target sou…