Robotics Motion Measurement

Multi-Agent Positioning and Trajectory Measurement

Compare multiple moving targets in one reference frame.

Lecen’s multi-agent positioning solution plans localization, trajectory recording and relative-motion analysis for mobile robots and multi-target experiments. Target identities, spatial calibration and time alignment organize observations for formation, crossing-path and coordination studies.

Product brand: Lecen Technology

Discuss the measurement task See how it works

Multi-Agent Positioning and Trajectory Measurement functional architecture illustration — Solution architecture illustration

Working scope: Multiple target identities
Approach: Shared space + time
Project focus: Coordination experiments

Project goals

Make multi-target motion comparable and reviewable

With several targets, visibility is only part of the problem. Identity stability, crossing paths and the timing of observations also matter. The design begins with defined targets, an observable volume and data validity; an advertised target count is not a substitute for a concurrent experiment in your space.

In focus

What the solution covers

Define targets in a common frame

Assign stable identifiers and references to each agent. Specify the relationship between measured position, orientation and the body frame so observations can be compared in one calibrated space.

Design for crossings and occlusion

Evaluate close encounters, formation changes and similar-looking targets. Camera views, target geometry and actual motion must be planned together to reduce association ambiguity.

Carry timing and validity with the data

Retain timestamps and distinguish valid, missing and estimated samples. Align observations before computing distances or formations so samples from different moments are not treated as simultaneous.

Analyze the cooperative task

Compare relative distances, crossing paths, formation changes and repeated trials with preserved raw tracks and processing methods. Plan export or research-tool integration around the required data interface.

Workflow

From multiple observations to coordinated analysis

Measurement and cooperative control are separate stages. Establish trustworthy observations in a common reference first.

Define agents
Set identifiers, body references and motion tasks.
Calibrate the volume
Cover the area and examine views and occlusions.
Record consistently
Collect position, applicable orientation, time and validity.
Compare the task
Replay and analyze relative motion, formations and exceptions.

Integration

Progress from single targets to concurrent trials

Validate each target definition before increasing the number and complexity of movements. Document conditions that were actually tested.

Multi-Agent Positioning and Trajectory Measurement workflow illustration — Workflow illustration

Describe the experiment

Specify count, size, speed, operating area and required outputs.

Design coverage and identity

Plan observation views, target components and common coordinates.

Check timing and interfaces

Evaluate timestamps, latency, updates and missing-data flags.

Test crossings and boundaries

Exercise encounters, formation changes, entry/exit and recovery, preserving trial records.

Configuration

Architecture and planning inputs

Multi-Agent Positioning and Trajectory Measurement — Architecture and planning inputs
Objects	Mobile robots or other defined targets within the experimental volume
Reference	Common coordinates, units, origin and body frames
Target data	Identity, position, applicable orientation, time and validity
Concurrency	Validated around size, speed, occlusion and spatial layout
Analysis	Relative motion, paths, formations and repeated trials
Integration	Data exchange matched to research tools and controller logs

Applications

Where it fits

Mobile-robot cooperation

Observe relative positions and crossing paths to compare algorithms.

Indoor formation experiments

Study formations and identity stability in a controlled volume with independent safety measures.

Multi-target motion evaluation

Compare collective paths, timing and exceptional intervals across strategies.

Application and workflow visuals

Multiple mobile robots in a position and trajectory observation concept; illustrates the application context.AI-generated concept, not a product test, software screenshot or customer project.

FAQ

Common questions

Can target count be determined from camera specifications alone?

No. Size, identification method, speed, occlusion and layout affect operation. Use representative concurrent trials.

Are all agents automatically on one clock?

Check timing definitions throughout capture, transport and reception. Equal update rates do not guarantee simultaneous observations.

How should occluded intervals be handled?

Preserve missing or estimated status and assess identity and trajectory recovery. Do not present interpolated samples as direct observations without distinction.

Does this include formation control or collision avoidance?

The scope is positioning, measurement and experimental analysis. Navigation, cooperative control and safety avoidance belong to their respective control systems and need separate integration validation.

Can indoor results be applied to every outdoor setting?

No. Changes in illumination, weather, range, visibility and target placement require renewed evaluation.

Project brief

Start with a project brief

Agents

Count, dimensions, target mounting and motion speed.

Area

Layout, boundaries, occlusions, lighting and independent safety arrangements.

Data

Frames, timing, interfaces, trial organization and comparison metrics.

Talk to Lecen

Let’s scope your project

Define targets, working volume, movement speeds and required outputs to discuss observation methods and validation.

Discuss the measurement task