16 citations · 57 across the 9 of their papers we have counts for
10 papers
Concurrent Optimization of Satellite Phasing and Tasking for Cislunar Space Situational Awareness
Malav Patel, Kento Tomita, Koki Ho
Recently, renewed interest in cislunar space spurred by private and public organizations has driven research for future infrastructure in the region. As Earth-Moon traffic increase…
Real-Time Stochastic Terrain Mapping and Processing for Autonomous Safe Landing
Kento Tomita, Koki Ho
Onboard terrain sensing and mapping for safe planetary landings often suffer from missed hazardous features, e.g., small rocks, due to the large observational range and the limited…
Cislunar Space Situational Awareness Constellation Design and Planning with Facility Location Problem
Yuri Shimane, Kento Tomita, Koki Ho
Driven by the surmounting interest for dedicated infrastructure in cislunar space, this work considers the satellite constellation design for cislunar space situational awareness (…
Sensitivity Analysis of Separation Time Along Weak Stability Boundary Transfers
Isabel Nolton, Kento Tomita, Yuri Shimane +1
This study analyzes the sensitivity of the dynamics around Weak Stability Boundary Transfers (WSBT) in the elliptical restricted three-body problem. With WSBTs increasing popularit…
Multi-Spacecraft Predictive Sensor Tasking for Cislunar Space Situational Awareness
Kento Tomita, Yuri Shimane, Koki Ho
This paper delves into the predictive sensor tasking algorithm for the multi-observer, multi-target sensor setting, leveraging the Extended Information Filter (EIF). Conventional p…
Stochastic Hazard Detection For Landing Under Topographic Uncertainty
Kento Tomita, Koki Ho
Autonomous hazard detection and avoidance is a key technology for future landing missions in unknown surface conditions. Current state-of-the-art stochastic algorithms assume simpl…
Deep Monocular Hazard Detection for Safe Small Body Landing
Travis Driver, Kento Tomita, Koki Ho +1
Hazard detection and avoidance is a key technology for future robotic small body sample return and lander missions. Current state-of-the-practice methods rely on high-fidelity, a p…
Deep Reinforcement Learning for Safe Landing Site Selection with Concurrent Consideration of Divert Maneuvers
Keidai Iiyama, Kento Tomita, Bhavi A. Jagatia +2
This research proposes a new integrated framework for identifying safe landing locations and planning in-flight divert maneuvers. The state-of-the-art algorithms for landing zone s…
Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing
Kento Tomita, Katherine A. Skinner, Koki Ho
Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the…
Semi-Analytical Model for Design and Analysis of On-Orbit Servicing Architecture
Koki Ho, Hai Wang, Paul A. DeTrempe +2
Robotic on-orbit servicing (OOS) is expected to be a key technology and concept for future sustainable space exploration. This paper develops a semi-analytical model for OOS system…