arXiv subjects

Mohan Rajesh Elara

Publications and source records attributed to Mohan Rajesh Elara.

6 recordsLinked to original sources

arXiv2026

Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots

Vision-Language Models (VLMs) are increasingly deployed as planners in robotic systems, where they translate natural-language commands into executable actions grounded in visual scene understanding. This tight coupling between perception and instruction-following introduces a new attack surface: adversarial text placed within the robot's visual field can act as an indirect prompt injection into the VLM's reasoning stack. We present a systematic study of physical prompt injection attacks against VLM-controlled sorting, introducing a four-category taxonomy, indirect signage, task redefinition, authority impersonation, and conflict injection, instantiated as a benchmark of 20 attack prompts evaluated across three physical scene layouts and three command formulations that vary in destination specificity and rule explicitness. Across 5,670 trials on three frontier VLMs (GPT-4o, Gemini 2.5 Flash, Qwen3-VL-32B), attacks succeed at 27.0%, 29.4%, and 5.0% respectively, with authority-impersonating and negation attacks transferring across all three models. Analysis of reasoning traces reveals that successful compromise is nearly always conscious (99.9% acknowledgment rate), and that models defend through structurally different mechanisms, explicit rejection for Gemini, perceptual inattention for GPT-4o. We evaluate three simple mitigations: prompt-based defense (75-100% effective, model-dependent), two-stage verification (85-100%), and pre-processing text masking (100%). Our findings show that VLM-controlled manipulation is meaningfully vulnerable to human-readable physical signage, and that simple defenses substantially reduce risk, though defense choice involves trade-offs. The defenses preserve general task capabilities in our benchmark, but they may impair tasks that require reading in-scene labels.

cs.RO↗

arXiv2025

A Scalable Post-Processing Pipeline for Large-Scale Free-Space Multi-Agent Path Planning with PiBT

Free-space multi-agent path planning remains challenging at large scales. Most existing methods either offer optimality guarantees but do not scale beyond a few dozen agents, or rely on grid-world assumptions that do not generalize well to continuous space. In this work, we propose a hybrid, rule-based planning framework that combines Priority Inheritance with Backtracking (PiBT) with a novel safety-aware path smoothing method. Our approach extends PiBT to 8-connected grids and selectively applies string-pulling based smoothing while preserving collision safety through local interaction awareness and a fallback collision resolution step based on Safe Interval Path Planning (SIPP). This design allows us to reduce overall path lengths while maintaining real-time performance. We demonstrate that our method can scale to over 500 agents in large free-space environments, outperforming existing any-angle and optimal methods in terms of runtime, while producing near-optimal trajectories in sparse domains. Our results suggest this framework is a promising building block for scalable, real-time multi-agent navigation in robotics systems operating beyond grid constraints.

cs.RO↗

arXiv2024

Time-Ordered Ad-hoc Resource Sharing for Independent Robotic Agents

Resource sharing is a crucial part of a multi-robot system. We propose a Boolean satisfiability based approach to resource sharing. Our key contributions are an algorithm for converting any constrained assignment to a weighted-SAT based optimization. We propose a theorem that allows optimal resource assignment problems to be solved via repeated application of a SAT solver. Additionally we show a way to encode continuous time ordering constraints using Conjunctive Normal Form (CNF). We benchmark our new algorithms and show that they can be used in an ad-hoc setting. We test our algorithms on a fleet of simulated and real world robots and show that the algorithms are able to handle real world situations. Our algorithms and test harnesses are opensource and build on Open-RMFs fleet management system.

cs.RO↗

arXiv2021

WaspL: Design of a Reconfigurable Logistic Robot for Hospital Settings

Healthcare poses diverse logistic requirements, which resulted in the deployment of several distinctly designed robots within a hospital setting. Each robot comes with its overheads in the form of, namely, none/limited scaling, dedicated charging stations, programming interface, closed architecture, training requirements, etc. This paper reports on developing a reconfigurable logistic robot named WaspL. The design of WaspL caters to the requirement of high mobility, open robotic operating system architecture, multi-functionality, and evolvability features. It fulfills multiple logistics modes, like towing, lifting heavy payloads, forklifting low ground clearance objects, nesting of two WaspL} etc., fulfilling different applications required in hospital settings. The design requirements, mechanical layout, and system architecture are discussed in detail. The finite element modeling, attribute-based comparison with other standard robots, are presented along with experimental results supporting the WaspL design capabilities.

cs.RO↗

arXiv2020

Securing Autonomous Service Robots through Fuzzing, Detection, and Mitigation

Autonomous service robots share social spaces with humans, usually working together for domestic or professional tasks. Cyber security breaches in such robots undermine the trust between humans and robots. In this paper, we investigate how to apprehend and inflict security threats at the design and implementation stage of a movable autonomous service robot. To this end, we leverage the idea of directed fuzzing and design RoboFuzz that systematically tests an autonomous service robot in line with the robot's states and the surrounding environment. The methodology of RoboFuzz is to study critical environmental parameters affecting the robot's state transitions and subject the robot control program with rational but harmful sensor values so as to compromise the robot. Furthermore, we develop detection and mitigation algorithms to counteract the impact of RoboFuzz. The difficulties mainly lie in the trade-off among limited computation resources, timely detection and the retention of work efficiency in mitigation. In particular, we propose detection and mitigation methods that take advantage of historical records of obstacles to detect inconsistent obstacle appearances regarding untrustworthy sensor values and navigate the movable robot to continue moving so as to carry on a planned task. By doing so, we manage to maintain a low cost for detection and mitigation but also retain the robot's work efficacy. We have prototyped the bundle of RoboFuzz, detection and mitigation algorithms in a real-world movable robot. Experimental results confirm that RoboFuzz makes a success rate of up to 93.3% in imposing concrete threats to the robot while the overall loss of work efficacy is merely 4.1% at the mitigation mode.

cs.CR↗

arXiv2020

Path tracking control of self-reconfigurable robot hTetro with four differential drive units

The research interest in mobile robots with independent steering wheels has been increasing over recent years due to their high mobility and better payload capacity over the systems using omnidirectional wheels. However, with more controllable degrees of freedom, almost all of the platforms include redundancy which is modeled using the instantaneous center of rotation (ICR). This paper deals with a Tetris inspired floor cleaning robot hTetro which consists of four interconnected differential-drive units, i.e., each module has a differential drive unit, which can steer individually. Differing from most other steerable wheeled mobile robots, the wheel arrangement of this robot changes because of its self-reconfigurability. In this paper, we proposed a robust path tracking controller that can handle discontinuous trajectories and sudden orientation changes. Singularity problems are resolved on both the mechanical aspect and control aspect. The controller is tested experimentally with the self-reconfigurable robotic platform hero, and results are discussed.

cs.RO↗