INRIA Sophia Antipolis
Abstract:Navigation among movable obstacles (NAMO) is a critical task in robotics, often challenged by real-world uncertainties such as observation noise, model approximations, action failures, and partial observability. Existing solutions frequently assume ideal conditions, leading to suboptimal or risky decisions. This paper introduces NAMOUnc, a novel framework designed to address these uncertainties by integrating them into the decision-making process. We first estimate them and compare the corresponding time cost intervals for removing and bypassing obstacles, optimizing both the success rate and time efficiency, ensuring safer and more efficient navigation. We validate our method through extensive simulations and real-world experiments, demonstrating significant improvements over existing NAMO frameworks. More details can be found in our website: https://kai-zhang-er.github.io/namo-uncertainty/
Abstract:Science teaching in secondary schools is often abstract for students. Even if some experiments can be conducted in classrooms, mainly for chemistry or some physics fields, mathematics is not an experimental science. Teachers have to convince students that theorems have practical implications. We present teachers an original and easy-to-use pedagogical tool: a cable-driven robot with a Web-based remote control interface. The robot implements several scientific concepts such as 3D-geometry and kinematics. The remote control enables the teacher to move freely in the classroom.