GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning

We present GLAS: Global-to- Local Autonomy Synthesis, a provably-safe, automated distributed policy generation for multi-robot motion planning. Our approach combines the advantage of centralized planning of avoiding local minima with the advantage of decentralized controllers of scalability and distributed computation. In particular, our synthesized policies only require relative state information of nearby neighbors and obstacles, and compute a provably-safe action. Our approach has three major components: i) we generate demonstration trajectories using a global planner and extract local observations from them, ii) we use deep imitation learning to learn a decentralized policy that can run efficiently online, and iii) we introduce a novel differentiable safety module to ensure collision-free operation, thereby allowing for end-to-end policy training. Our numerical experiments demonstrate that our policies have a 20% higher success rate than optimal reciprocal collision avoidance, ORCA, across a wide range of robot and obstacle densities. We demonstrate our method on an aerial swarm, executing the policy on low-end microcontrollers in real-time

CaRT: Certified Safety and Robust Tracking in Learning-based Motion Planning for Multi-Agent Systems

The key innovation of our analytical method, CaRT, lies in establishing a new hierarchical, distributed architecture to guarantee the safety and robustness of a given learning-based motion planning policy. First, in a nominal setting, the analytical form of our CaRT safety filter formally ensures safe maneuvers of nonlinear multi-agent systems, optimally with minimal deviation from the learning-based policy. Second, in off-nominal settings, the analytical form of our CaRT robust filter optimally tracks the certified safe trajectory, generated by the previous layer in the hierarchy, the CaRT safety filter. We show using contraction theory that CaRT guarantees safety and the exponential boundedness of the trajectory tracking error, even under the presence of deterministic and stochastic disturbance. Also, the hierarchical nature of CaRT enables enhancing its robustness for safety just by its superior tracking to the certified safe trajectory, thereby making it suitable for off-nominal scenarios with large disturbances. This is a major distinction from conventional safety function-driven approaches, where the robustness originates from the stability of a safe set, which could pull the system over-conservatively to the interior of the safe set. Our log-barrier formulation in CaRT allows for its distributed implementation in multi-agent settings. We demonstrate the effectiveness of CaRT in several examples of nonlinear motion planning and control problems, including optimal, multi-spacecraft reconfiguration.Comment: IEEE Conference on Decision and Control (CDC), Preprint Version, Accepted July, 202

Paradox in the pursuit of a critical theorization of the development of self in family relationships

This article starts with my dissatisfaction with the post-structuralist treatment of the production of subjectivity within regulatory discourses and practices due to its neglect of psychological processes. Taking starting points from within the history set out in the previous article, it highlights the paradox for critical psychologists like myself involved in both applying a post-structuralist critique to 'psy' discourses and trying to theorize subjectivity in a way that goes beyond the dualism of individual and society, of psychology and sociology. The relational, or intersubjective, approach to self that originates in object relations psychoanalysis as it emerged in the mid-20th-century UK is central to both of these activities; object of the former and resource for the latter. I explore the paradox that this creates for critical psychology, both epistemological and ontological. In aiming to provide a psycho-social account of self in family relationships, I deploy the radical conceptualisation of intersubjectivity initiated in British object relations theory as a way of going beyond both the individualized self and the neglect of psychological processes in constructionist theorizing subjectivity

The North Atlantic Waveguide and Downstream Impact Experiment

The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft, each with a sophisticated set of remote sensing and in situ instruments, and coordinated with a suite of ground-based measurements. A total of 49 research flights were performed, including, for the first time, coordinated flights of the four aircraft: the German High Altitude and Long Range Research Aircraft (HALO), the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 September to 22 October 2016 with frequently occurring extratropical and tropical cyclones was ideal for investigating midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, as well as their dynamic interaction with the jet stream, subsequent development, and eventual downstream weather impact on Europe. Examples are presented to highlight the wealth of phenomena that were sampled, the comprehensive coverage, and the multifaceted nature of the measurements. This unique dataset forms the basis for future case studies and detailed evaluations of weather and climate predictions to improve our understanding of diabatic influences on Rossby waves and the downstream impacts of weather systems affecting Europe

Do Robots Dream of Random Trees? Monte Carlo Tree Search for Dynamical, Partially Observable, and Multi-Agent Systems

Autonomous robots are poised to transform various aspects of society, spanning transportation, labor, and scientific space exploration. A critical component to enable their capabilities is the algorithm that interprets sensor data to generate intelligent planned behavior. Although reinforcement learning methods that train parameterized policies offline from data have shown recent success, they are inherently limited when robots inevitably encounter situations outside their training domain. In contrast, optimal control techniques, which compute trajectories in real-time using numerical optimization, typically yield only locally optimal solutions. This research endeavors to bridge the gap by developing algorithms that compute trajectories in real-time while converging towards globally optimal solutions. Building upon the Monte Carlo Tree Search (MCTS) framework—a stochastic tree search method that simulates future trajectories while balancing exploration and exploitation—the research focus is twofold: (i) constructing an efficient discrete representation of continuous systems in a decision trees, and (ii) searching on the resulting tree while balancing exploration and exploitation to achieve global optimality. The study spans theoretical analysis, algorithmic design, and hardware demonstrations across dynamical, partially observable, and multi-agent systems. By addressing these critical questions, this research aims to advance the field of autonomous robotics, enabling the deployment of intelligent robots in complex and diverse environments.</p

Hydrochlorothiazide-induced hepatotoxicity: A rare case of DILI.

International audienceThiazide diuretics are prescribed daily and rarely hepatotoxic. We report the case of 86-year-old woman who was admitted in hospital for jaundice after taking hydrochlorothiazide. All differential diagnoses have been eliminated. The liver biopsy was compatible with drug-induced hepatitis. Clinical and biological manifestations improved after discontinuation of the treatment. The reported case is compared to three other cases in the literature

Exposure to pesticide residues and contaminants of the vegetarian population—French data

In the present chapter, dietary exposures of different vegetarian populations to pesticide residues as well as those to contaminants are discussed, based on French data. For 48 pesticide residues out of 421, it was shown that, based on theoretical calculation of the exposure, vegetarians could have higher exposures than those of the general population, the pescetarian population being very close to the situation observed for the general population. On the other hand, biomonitoring studies demonstrated that there was a trend toward lower organochlorine contamination in the vegan population compared to that of the general population. With regard to contaminants, exposures to phytoestrogens or to some trace elements (Cd, Al, Ni) were higher for the vegetarian population compared to those of the general population. Otherwise, the vegetarian population studied in the present study was less exposed than the general population to other contaminants such as some persistent organic pollutants, some mycotoxins, and some trace elements