33 accepted papers
Mobile robots deployed for persistent operations in partially known environments need to be able to recover and adapt against unforeseen changes in dynamics, e.g., due to failures, or external disturbances. This paper presents a novel hierarchical framework capable of zero-shot adaptation to environ…
In communicationless environments, multi-robot systems must operate without the constant information exchange that many coordination strategies typically assume. This paper presents a novel dynamic epistemic planning framework that enables implicit coordination and long horizon planning through high…
This paper presents a novel theory of mind (ToM)-based approach for implicit coordination of multi robot systems (MRS) in environments where direct communication is unavailable. The proposed approach integrates higher-order reasoning, epistemic theory, and active inference to coordinate the actions
Motion planning failures during autonomous navigation often occur when safety constraints are either too conservative, leading to deadlocks, or too liberal, resulting in collisions. To improve robustness, a robot must dynamically adapt its safety constraints to ensure it reaches its goal while balan
Autonomous mobile robots (AMRs) equipped with high-quality cameras are revolutionizing the field of autonomous photography by delivering efficient and cost-effective methods for capturing dynamic visual content. As AMRs are deployed in increasingly diverse environments, the challenge of consistently
Humans interacting with robots often form predictions of what the robot will do next. For instance, based on the recent behavior of an autonomous car, a nearby human driver might predict that the car is going to remain in the same lane. It is important for the robot to understand the human’s predict
Localization is one of the most important tasks for mobile robot operations. Without such capability, a robot may wander toward unsafe states and never complete a desired task. Such capability is even more important in multi-robot system (MRS) operations in which their motion is coordinated based on…
For autonomous mobile robots, uncertainties in the environment and system model can lead to failure in the motion planning pipeline, resulting in potential collisions. In order to achieve a high level of robust autonomy, these robots should be able to proactively predict and recover from such failur…
A common challenge for mobile robots is traversing uncertain environments containing obstacles, rough terrain, or hazards. Without full knowledge of the environment, an unmanned ground vehicle (UGV) navigating towards a goal could easily drive down a path that is blocked (requiring the robot to retr
As Multi-Robot Systems (MRS) become more affordable and computing capabilities grow, they provide significant advantages for complex applications such as environmental monitoring, underwater inspections, or space exploration. However, accounting for potential communication loss or the unavailability
Autonomous mobile robots (AMR) operating in the real world often need to make critical decisions that directly impact their own safety and the safety of their surroundings. Learning-based approaches for decision making have gained popularity in recent years, since decisions can be made very quickly…
Current motion planning approaches for autonomous mobile robots often assume that the low level controller of the system is able to track the planned motion with very high accuracy. In practice, however, tracking error can be affected by many factors, and could lead to potential collisions when the…
In applications such as search and rescue or disaster relief, heterogeneous multi-robot systems (MRS) can provide significant advantages for complex objectives that require a suite of capabilities. However, within these application spaces, communication is often unreliable, causing inefficiencies or…
In communication restricted environments, a multi-robot system can be deployed to either: i) maintain constant communication but potentially sacrifice operational efficiency due to proximity constraints or ii) allow disconnections to increase environmental coverage efficiency, challenges on how, whe…
Agile navigation through uncertain and obstacle-rich environments remains a challenging task for autonomous mobile robots (AMR). For most AMR, obstacles are identified using onboard sensors, e.g., lidar or cameras. The effectiveness of these sensors may be severely limited, however, by occlusions in…
Navigation through unknown, cluttered environments is a fundamental and challenging task for autonomous vehicles as they must deal with a myriad of obstacle configurations typically unknown a priori. Challenges arise because obstacles of unknown shapes and dimensions can create occlusions limiting s…
A majority of collision avoidance and motion planning algorithms deployed on autonomous mobile robots tend to be reactive to the presence and motion of nearby dynamic actors. While these algorithms can produce collision free navigation, they do not necessarily follow social protocol and exhibit unna
The lack of communication between agents in a multi-robot system is often regarded as a limiting factor that can affect and delay cooperative exploration and exploitation of cluttered and uncertain environments. On the contrary, this paper proposes a complete planning framework to enable cooperative…
This paper addresses a safe planning and control problem for mobile robots operating in communication- and sensor-limited dynamic environments. In this case the robots cannot sense the objects around them and must instead rely on intermittent, external information about the environment, as e.g., in…
Changes in model dynamics due to factors like actuator faults, platform aging, and unexpected disturbances can challenge an autonomous robot during real-world operations affecting its intended behavior and safety. Under such circumstances, it becomes critical to improve tracking performance, predict
Cyber-attacks, failures, and implementation errors inside the controller of an autonomous system can affect its correct behavior leading to unsafe states and degraded performance. In this paper, we focus on such problems specifically on cyber-attacks that manipulate controller parameters like the ga…
This paper presents a novel method for transferring motion planning and control policies between a teacher and a learner robot. With this work, we propose to reduce the sim-to-real gap, transfer knowledge designed for a specific system into a different robot, and compensate for system aging and fail…
Due to changes in model dynamics or unexpected disturbances, an autonomous robotic system may experience unforeseen challenges during real-world operations which may affect its safety and intended behavior: in particular actuator and system failures and external disturbances are among the most commo…
A resilient multi-vehicle system cooperatively performs tasks by exchanging information, detecting, and removing cyber attacks that have the intent of hijacking or diminishing performance of the entire system. In this paper, we propose a framework to: i) detect and isolate misbehaving vehicles in th…
Autonomous vehicles may not behave as expected when subject to environmental disturbances. For instance, control commands suitable for driving on dry, paved roads may lead to unsafe conditions and undesired deviations when on slippery dirt or icy roads. Furthermore, it becomes increasingly important…
Mobile robots are traditionally developed to be reactive and avoid collisions with surrounding humans, often moving in unnatural ways without following social protocols, forcing people to behave very differently from human-human interaction rules. Humans, on the other hand, are seamlessly able to un…
Navigation through an occluded environment is a challenging task for autonomous mobile robots (AMR), since they must balance both safety and speed in an attempt to fluidly steer around occlusions in uncertain environments. This is because real world environments have dynamic actors that may be occlu
For safe and efficient human-robot interaction, a robot needs to predict and understand the intentions of humans who share the same space. Mobile robots are traditionally built to be reactive, moving in unnatural ways without following social protocol, hence forcing people to behave very differently…
Autonomous vehicles are typically developed and trained to work under certain system and environmental conditions defined at design time and can fail or perform poorly if unforeseen conditions such as disturbances or changes in model dynamics appear at runtime. In this work, we present a fast online…
Autonomous robots, especially aerial vehicles, when subject to disturbances, uncertainties, and noises may experience variations from their desired states and deviations from the planned trajectory which may lead them into an unsafe state (e.g., a collision). It is thus necessary to monitor their st
In this paper, we present a fast run-time monitoring framework for safety assurance during autonomous system operations in uncertain environments. Modern unmanned vehicles rely on periodic sensor measurements for motion planning and control. However, a vehicle may not always be able to obtain its st…
Modern unmanned aerial vehicles (UAVs) rely on constant periodic sensor measurements to detect and avoid obstacles. However, constant checking and replanning are time and energy consuming and are often not necessary especially in situations in which the UAV can safely fly in uncluttered environments…
In this paper we consider an online planning problem for unmanned aerial vehicle (UAV) operations. Specifically, a UAV has the task of reaching a goal from a set of possible goals while minimizing the amount of energy required. Due to unforeseen disturbances, it is possible that initially attractive…